Senior Data & AI Quality Engineer (Ingestion · Evaluation · Testing)

Senior Quality Engineer

Notice Period: Immediate

Purpose of the Job:

We are seeking a highly skilled and experienced Senior Quality Engineer to join our Enterprise Technology and Data team. This role is crucial in ensuring the delivery of high-quality data-driven solutions and applications across our enterprise systems. The ideal candidate will have deep expertise in quality engineering, automated testing, and extensive experience in testing large-scale data systems, particularly in ETL processes and working with Azure Fabric and Google Cloud data platforms such as BigQuery and Google Cloud Data Pipelines.

As a Senior Quality Engineer, you will be responsible for defining and implementing quality assurance processes, developing automated tests, identifying and mitigating risks, and ensuring the overall quality of our technology and data platforms across multi-cloud environments (Azure and Google Cloud Platform). You will work closely with cross-functional teams including developers, data engineers, and product managers to ensure that the highest standards of quality are maintained throughout the software development lifecycle.

Main Activities:

1. · Test Planning & Execution: Design detailed test strategies/plans, test cases, and test scripts to validate data accuracy, integrity, and system functionality in ETL pipelines across Azure and GCP (e.g., Dataflow, Data Fusion, BigQuery pipelines), including both functional and non-functional testing.
2. · Data Quality: Collaborate with data engineers to monitor and ensure the accuracy, completeness, and consistency of data across various data platforms including Azure Synapse/Fabric and Google BigQuery, validating transformations and data integrity in ETL pipelines.
3. · Data Pipeline Testing: Collaborate with data engineering teams to design and execute tests for Data pipelines running on Azure Fabric as well as Google Cloud services such as Dataflow, Dataproc, and Pub/Sub-based pipelines, ensuring transformation, integration, and storage processes function as expected.
4. · SQL Database Testing: SQL Database Testing: Development and execution of SQL-based automated tests for database validation, ensuring data integrity, performance, and security across multiple databases including BigQuery datasets and Azure SQL/Synapse environments.
5. · Performance Testing: Conduct performance testing to evaluate the scalability, stability, and performance of large-scale data systems across distributed cloud platforms including Azure and GCP.
6. · Automated Testing: Develop and maintain automated test frameworks for data applications, including ETL processes, APIs, and data integration systems using industry-standard tools, and extend automation to support BigQuery validation, GCP pipeline testing, and AI/ML data validation scenarios.
7. · Defect Tracking & Resolution: Work with development and operations teams to identify, report, and track defects across multi-cloud data ecosystems, ensuring timely resolution.
8. · Continuous Improvement: Propose and implement improvements to testing processes and frameworks to increase efficiency and effectiveness of quality assurance efforts across Azure and Google Cloud-based data platforms and AI-enabled data solutions.
9. · Collaboration: Partner with business stakeholders, project managers, and technical teams to ensure alignment with quality goals and deliverables across enterprise data platforms spanning multiple cloud providers.
10. · Mentorship: Provide guidance and mentorship to junior quality engineers, helping them improve their technical skills in modern data testing practices including cloud-native and AI-driven validation techniques.
11. · Compliance & Best Practices: Ensure adherence to industry standards and best practices related to software quality, particularly in relation to data systems, ETL processes, and cloud technologies including Azure and Google Cloud Platform environments.

Knowledge/Skill Requirements:

· Education:

1. o Bachelor’s degree in computer science, Information Technology, Engineering, or a related field.
2. · Experience:
3. o 5+ years of experience in software quality engineering, with at least 3 years of experience in an enterprise data environment.
4. o Proven experience in automated testing tools (e.g., Selenium, JUnit, TestNG, or similar frameworks).
5. o Hands-on experience with data validation, transformation, and data pipeline testing in cloud environments, specifically Azure and/or Google Cloud Platform (GCP).
6. o Strong understanding of data management, data warehousing, ETL processes, and data integration.
7. o Experience with data warehousing, data lakes, and cloud-based ETL tools including Azure Data Factory, Azure Synapse, Google BigQuery, Dataflow, and Dataproc is a plus.

Technical Skills:

1. o Proficient in scripting languages (e.g., Python, Java, SQL) for test automation and ETL process validation.
2. o Experience working with Azure Data Factory, Azure Synapse Analytics, Microsoft Fabric, as well as Google Cloud services such as BigQuery, Dataflow and Cloud Composer (Airflow) for data pipeline orchestration and validation.
3. o Strong knowledge of software development methodologies (Agile, Scrum, Waterfall) and experience in a continuous integration/continuous deployment (CI/CD) environment.
4. o Familiarity with version control systems (e.g., Git), CI/CD tools (e.g., Jenkins, Azure DevOps), and cloud infrastructure (e.g., Azure, GCP).
5. · Soft Skills:
6. o Strong analytical, problem-solving, and troubleshooting skills.
7. o Excellent communication skills, with the ability to collaborate effectively across departments.
8. o Detail-oriented with a passion for ensuring high-quality standards in data-driven solutions.
9. o Ability to work independently and as part of a team, managing multiple priorities in a fast-paced environment.
10. · Certifications/Additional Training – Nice-to-Have:
11. o Relevant certifications (e.g., Azure DevOps, Azure ML, ISTQB, Google Cloud Professional Data Engineer or Professional Cloud Developer) are a plus.
12. o Experience working with data governance tools such as Azure Purview and ensuring data compliance

About the team

SecurITe’s mission is to build an Agentic‑AI driven security platform that protects critical infrastructure from modern cyber threats. Our focus is on delivering highly performant, resilient, and intelligent network security systems that help defenders stay ahead of adversaries.

About the Role

We’re looking for a seasoned Senior Quality Engineer to provide technical leadership and architectural oversight for our next‑generation cybersecurity AI platform. In this high-impact role, you will define the technical strategy for quality assurance, ensuring our agentic AI transforms cyber defense with unparalleled reliability.

You will be responsible for the end-to-end quality lifecycle, from architectural reviews to the deployment of scalable automation frameworks. Beyond technical execution, you will serve as a mentor to junior team members, fostering a culture of technical excellence and driving the strategy that ensures our solutions meet the rigorous demands of critical infrastructure protection.

What You’ll Do

●    Defining and driving comprehensive QA strategies and roadmaps for the cybersecurity platform.

●    Designing, developing, and executing test plans, test cases, and automated scripts to ensure software quality.

●    Performing functional, regression, performance, scalability and security testing to identify bugs or defects.

●    Collaborating with developers, product managers, and other stakeholders to understand product requirements and testing needs.

●    Identifying, documenting, and tracking software defects, ensuring clear communication of issues and their resolutions.

●    Leading deep-dive root-cause analysis for critical system defects and security vulnerabilities.

●    Conducting thorough reviews of product specifications and software design to identify potential areas of concern before testing.

●    Architecting and designing complex, scalable test automation frameworks to optimize CI/CD velocity.

●    Ensuring the software meets customer and business requirements by validating the functionality and performance.

●    Assisting in continuously improving QA processes, tools, and best practices to enhance software testing efficiency and effectiveness.

●    Supporting user acceptance testing (UAT) and assisting clients with product validation.

●    Mentoring junior and mid-level engineers, providing technical guidance and conducting architectural reviews.

Required Experience

●    A Bachelor’s degree in Computer Science, Information Technology, Computer Engineering, or a related field.

●    8-10 years of proven experience in quality engineering, specifically within network cybersecurity, Identity Providers, or AI-integrated platforms.

●    Expertise in manual and automated testing.

●    Deep domain expertise in complex system validation and advanced automation practices at scale.

●    Proficiency in programming languages like Python to build and run automated test scripts.

●    "Strong knowledge of software testing methodologies, performance testing tools (e.g., JMeter, k6), and security traffic generation/simulation tools (e.g., Ixia BreakingPoint, Scapy, or Snort/Suricata traffic generators)."

●    Understanding of continuous integration/continuous deployment (CI/CD) pipelines and version control systems like Git.

●    Strong communication skills for documenting test results and interacting with cross-functional teams.

●    Excellent analytical skills, attention to detail, and problem-solving ability.

●    Ability to work independently as well as collaboratively in a team environment.

●    A curious mindset with a willingness to quickly learn new technologies and testing tools.

Required Skills & Qualifications

●    Familiarity with cloud-based testing environments (GCP, AWS, Azure).

●    Experience with cybersecurity products or cloud services or IDP or Web UI

The Mindset

●    Problem Solver: You thrive on complex, ambiguous challenges and engineer elegant solutions.

●    Ownership‑Driven: You take initiative, move fast, and deliver outcomes without hand‑holding.

●    Continuous Learner: You stay ahead of the curve in AI, ML, and emerging technologies.

●    Startup DNA: You excel in fast‑moving environments where priorities evolve and impact is immediate.

Principal Software Engineer

Location: Bangalore India

Department: AI Engineering / Quality Assurance

Experience Level: Mid to Senior

We are looking for a highly motivated Senior AI Test / Automation Engineer to design and scale automated validation frameworks for AI/ML models, LLM-based applications, and agentic systems. This role is critical to ensure that AI solutions meet enterprise standards for quality, reliability, safety, and compliance before and after production deployment.

Key Responsibilities

• Build and maintain AI test automation frameworks for pre-qualification and continuous validation of models and agent workflows
• Develop comprehensive test suites, including:
• Unit, integration, and end-to-end (E2E)
• Functional, regression, performance, and safety testing
• Validate AI system behavior, including:
• Non-deterministic LLM outputs
• Hallucinations and edge cases
• Multi-step agent decision-making
• Design and manage evaluation systems:
• Golden datasets
• Benchmarking pipelines (accuracy, latency, reliability)
• Automate testing within CI/CD pipelines for model updates, prompt changes, and tool integrations
• Implement observability and telemetry to enable traceability, monitoring, and audit readiness
• Collaborate cross-functionally with ML, MLOps, Product, and Security teams to define quality gates and release criteria
• Track and report quality KPIs, including test coverage, defect leakage, and system reliability
• Drive root-cause analysis and continuous improvement across the AI testing lifecycle

Required Skills

Core Engineering

• Strong programming skills in Python; familiarity with Bash, TypeScript, or Go
• Experience with test automation frameworks such as PyTest, Playwright, Selenium, or Cypress
• Proficiency in CI/CD tools (GitHub Actions, Jenkins, GitLab CI)
• Experience with cloud platforms (AWS, Azure, GCP) and containers (Docker, Kubernetes)

AI / ML & Agentic Systems

• Hands-on experience with LLM ecosystems (OpenAI, Anthropic, Bedrock)
• Familiarity with:
• RAG architectures and vector databases (Pinecone, Weaviate)
• Agent frameworks (LangChain, LlamaIndex, AutoGen)

AI Testing Techniques

• Experience with non-deterministic testing approaches (statistical assertions, tolerance thresholds)
• Knowledge of evaluation methods:
• LLM-as-a-judge
• BLEU, ROUGE, semantic similarity scoring
• Experience with prompt and agent regression testing
• Understanding of AI safety testing, including adversarial testing, bias/fairness validation, and jailbreak detection

Tooling (Preferred)

• AI testing & observability tools: LangSmith, TruLens, Arize, Weights & Biases
• Evaluation tools: DeepEval, Ragas, PromptFoo, Giskard
• Monitoring: Prometheus, Grafana, OpenTelemetry

Soft Skills

• Strong analytical and problem-solving skills
• Excellent communication and cross-functional collaboration
• Data-driven mindset with focus on quality KPIs
• Detail-oriented with a strong bias toward automation and scalability

Experience Requirements

• 7+ years in QA, SDET, or test automation engineering
• Proven experience building and scaling automation frameworks
• Hands-on experience with AI/ML systems or LLM-based applications
• Experience testing RAG pipelines or agentic workflows
• Owned end-to-end AI test strategy and architecture
• Defined quality metrics and release gates
• Delivered scalable validation pipelines for production AI systems
• Supported audit and compliance readiness

Preferred

• Experience in enterprise or regulated environments (SOC2, ISO 27001, etc.)
• Exposure to:
• Shift-left testing practices
• Production observability and monitoring
• Chaos or resilience testing

Senior-Level Differentiators

Education

• Bachelor’s or Master’s degree in Computer Science, Software Engineering, or related field

Nice-to-have:

• ISTQB certification
• Cloud/ML certifications (AWS, Azure, GCP)
• AI testing certifications

What Success Looks Like

• AI systems that are accurate, reliable, and safe
• Fully automated test pipelines integrated into CI/CD
• Measurable improvements in defect leakage and model quality
• Strong observability and auditability across AI systems
• Scalable validation frameworks supporting rapid AI innovation

About Us

We believe the future of software development is AI-native — where engineers operate at a higher level of abstraction and quality remains non-negotiable. 

Incubyte is a software craft consultancy where the “how” of building software matters as much as the “what”.  

We partner with companies of all sizes, from helping enterprises build, scale, and modernize to early-stage founders bring their ideas to life. 

Our engineers operate in an AI-native development model, using AI as a collaborator across the SDLC to accelerate development while upholding the discipline of software craftsmanship. Guided by Software Craftsmanship and Extreme Programming practices, we build reliable, maintainable, and scalable systems with speed, without compromising quality. If this way of building software resonates with you, we’d like to talk. 

Our Guiding Principles 

These principles define how we work at Incubyte. They are non-negotiable. 

Relentless Pursuit of Quality with Pragmatism 

  We build high-quality systems without losing sight of delivery. 

Extreme Ownership 

  We take responsibility end-to-end for decisions, execution, and outcomes. 

Proactive Collaboration 

  We collaborate closely, challenge each other, and solve problems together. 

Active Pursuit of Mastery 

  We continuously improve our craft and raise our bar. 

Invite, Give, and Act on Feedback 

We seek, give, and act on feedback to get better every day. 

Ensuring Client Success 

We act as trusted partners and focus on real outcomes, not just output. 

Job Description

This is a remote position.

Experience Level

2+ years of experience in SQL, Python, and Snowflake (or equivalent cloud data warehouse), Azure Cloud services.

Role Overview

If you're a Data Craftsperson who takes pride in clean, well-tested data solutions and believes in the principles of Extreme Programming, we'd love to meet you. At Incubyte, we're a DevOps organization where developers own the entire release cycle — you'll get hands-on experience across data engineering, analytics, cloud infrastructure, and direct client communication. This role sits primarily in data engineering (80%) with a meaningful analytics component (20%), supporting our client's data systems end-to-end.

What You'll Do

• Design, build, and maintain data pipelines and infrastructure using SQL and Python
• Work within Snowflake to build and optimize data models supporting business use cases
• Parse and process structured and semi-structured data (JSON, XML) from varied sources
• Diagnose issues across raw, intermediate, and summary tables
• Build SQL queries to support repeatable analytics use cases based on stakeholder requirements
• Investigate and resolve data quality issues, including time-sensitive or urgent ones
• Identify opportunities to consolidate models and maintain a single source of truth (SSOT)

Requirements

What We're Looking For

• 2+ years of experience with SQL and relational databases, with the ability to understand complex data relationships and transformations (required)
• 2+ years of experience with Python for data engineering tasks (required)
• Experience with Snowflake or an equivalent cloud data warehouse (required)
• Experience working with Snowflake Coco or any other AI tools(required) 
• Experience parsing JSON and XML data (a plus)
• A strong eye for data quality and attention to detail
• Knowledge of Git (required)
• Knowledge of Azure cloud services such as Azure Data Factory, Azure Blob Storage, and Azure SQL Database (required)
• Knowledge of data infrastructure/modeling tools like DBT, Fivetran (a plus)
• Experience with BI tools like Power BI(a plus, not core to this role)
• Knowledge of Docker, Linux, Shell/Bash, and virtualization technologies (a plus)
• Knowledge of SSIS packages (a plus)
• Familiarity with CI/CD methodologies

Benefits

Life at Incubyte  

We are a remote-first company with structured flexibility. Teams commit to shared rhythms during core hours, ensuring smooth collaboration while maintaining autonomy. Twice a year, we come together in person for a co-working sprint and once a year for a retreat - with all travel expenses covered. 

Our environment is built for crafters: pairing, refactoring, experimenting with AI, and pushing the boundaries of software excellence. We are all lifelong learners, and our work is our passion. 

Perks

• Dedicated learning & development budget. 
• Sponsorship for conference talks. 
• Comprehensive medical & term insurance.
• Employee-friendly leave policies. 
• Home Office fund 
• Medical Insurance

Location – Hyderabad (Hybrid)

Work Experience – 5 to 7 years

CTC – upto 20 LPA

Roles & Responsibilities:

· We are looking for a Senior Data Engineering who will be majorly responsible for designing, building and maintaining ETL/ ELT pipelines.

· Integration of data from multiple sources or vendors to provide the holistic insights from data.

· You are expected to build and manage Data warehouse solutions, designing data models, creating ETL processes, implementing data quality mechanisms etc.

· Performs EDA (exploratory data analysis) required to troubleshoot data related issues and assist in the resolution of data issues.

· Should have experience in client interaction.

· Experience in mentoring juniors and providing required guidance.

Required Technical Skills

· Extensive hands on experience in Python, Pyspark, SQL, Dataiku.

· Strong experience in Data Warehouse, ETL, Data Modelling, building ETL Pipelines, Snowflake database.

· Working knowledge in Databricks, Redshift, ADF etc.

· Hands-on experience in cloud services like Azure, AWS- S3, Glue, Lambda, CloudWatch, Athena.

· Sound knowledge in end-to-end Data management, Data ops, quality and data governance.

· Familiar with SFDC, Waterfall/ Agile methodology.

· Strong domain knowledge in Pharma domain/ life sciences commercial data operations.

Qualifications

· Bachelor’s or master’s Engineering/ MCA or equivalent degree.

· 5-7 years of relevant industry experience as Data Engineer.

· Experience working on Pharma syndicated data such as IQVIA, Veeva, Symphony; Claims, CRM, Sales etc.

· High motivation, good work ethic, maturity, self-organized and personal initiative.

· Ability to work collaboratively and providing the support to the team.

· Excellent written and verbal communication skills.

· Strong analytical and problem-solving skills. 

Sr. Data Engineer 

Location: Pune

Responsibilities 

· Lead the end-to-end design and development of scalable, high-performance data pipelines and ETL/ELT frameworks aligned with modern data engineering best practices. 

· Architect complex data integration workflows that bring together structured, semi-structured, and unstructured data from both cloud and on-premise sources. 

· Build robust real-time, batch, and on-demand pipelines with built-in observability—monitoring, alerting, and automated error handling. 

· Partner with analysts, data scientists, and business leaders to define and deliver reliable data models, quality frameworks, and SLAs that power key business insights. 

· Ensure optimal pipeline performance and throughput, with clearly defined SLAs and proactive alerting for data delivery or quality issues. 

· Collaborate with platform, DevOps, and architecture teams to build secure, reusable, and CI/CD-enabled data workflows that align with enterprise architecture standards. 

· Establish and enforce the best practices in source control, code reviews, testing automation, and continuous delivery for all data engineering components. 

· Lead root cause analysis (RCA) and preventive maintenance for critical data failures, ensuring minimal business impact and continuous service improvement. 

· Guide the team in establishing standards for data modeling, transformation logic, and governance, ensuring long-term maintainability and scalability. 

· Design and execute comprehensive testing strategies—unit, integration, and system testing—ensuring high data reliability and pipeline resilience. 

· Monitor and fine-tune data pipeline and query performance, optimizing for reliability, scalability, and cost-efficiency. 

· Create and maintain detailed technical documentation, including data architecture diagrams, process flows, and integration specifications for internal and external stakeholders. 

· Facilitate and lead discussions with business and operational teams to understand data requirements, prioritize initiatives, and drive data strategy forward. 

Qualifications 

· 7 to 10 years of hands-on experience in data engineering roles with a proven record of building scalable and secure data platforms. 

· Over 5 years of experience in scripting languages such as Python for data processing, automation, and ETL development. 

· 4+ years of experience with Snowflake, including performance tuning, security model design, and advanced SQL development. 

· 5+ years of experience with data integration tools such as Azure Data Factory, Fivetran, or Matillion. 

· 5+ years of experience in writing complex, highly optimized SQL queries on large datasets. 

· Proven experience integrating and managing APIs, JSON, XML, and webhooks for data acquisition. 

· Hands-on experience with cloud platforms (Azure/AWS) and orchestration tools like Apache Airflow or equivalent. 

· Experience with CI/CD pipelines, automated testing, and code versioning tools (e.g., Git). 

· Familiarity with dbt or similar transformation tools and best practices for modular transformation development. 

· Exposure to data visualization tools like Power BI for supporting downstream analytics is a plus. 

· Strong interpersonal and communication skills with the ability to lead discussions with technical and business stakeholders. 

Education 

Bachelor’s or Master’s degree in Computer Science/Information technology or related field. 

Equivalent academic and work experience can be considered. 

Total exp: 5-8 Years

Client: MRI Software

Location: Vadodara

Budget: Look for decent with experience

Mode interview: 1 Virtual

Mode of Work: Hybrid

QA Engineer:

Job Summary/Objective 

Quality Assurance Engineers at MRI collaborate closely with Product Management and Product Development teams to deliver high-quality, high-performance products for our clients. In this role, QA Engineers are responsible for creating and contributing to the documentation of user stories and acceptance criteria, working alongside product owners and development teams. They define manual and automation testing strategies, tools, scenarios, and plans for both web and mobile products, ensuring comprehensive functional and performance testing. 

 QA Engineers will execute static, dynamic, and performance testing while providing detailed reporting and feedback throughout the development lifecycle. They are expected to demonstrate strong technical skills, including expertise in back-end development, database queries, and keen attention to detail. Effective written, verbal, and organizational communication is essential. 

 In addition, QA Engineers will leverage AI to optimize and automate repetitive tasks, thereby enhancing the overall efficiency and effectiveness of QA processes, ensuring a faster, more accurate testing cycle.

Tools and technology:

1.     Tools: Jira, Xray, TFVC, Git

2.     API: REST, SOAP, SoapUI, Postman

3.     Automation: C#, JavaScript, TypeScript, Ruby, Playwright, SpecFlow

4.     Database: SQL

Senior QA Engineer

Make quality part of the engineering system.

AbleCredit builds software for complex enterprise workflows where AI, APIs, business rules, human decisions, and real-world operations have to work together reliably. We care about building products that work in production - not just in demos. We're looking for a senior quality engineer who can move quality upstream: from release-time testing to better automation, contracts, observability, and engineering practices.

What You'll Own?

• Own quality strategy across web, mobile, backend APIs, integrations, and end-to-end workflows.

• Design and maintain automated regression suites for critical customer journeys.

• Build API, integration, contract, and workflow tests that catch failures before production.

• Partner with engineering and product teams during design - not only after development is complete.

• Define release readiness, risk-based testing, and production validation practices.

• Investigate escaped defects, identify systemic causes, and drive preventive improvements.

• Improve test data, environments, tooling, and CI integration so teams can ship confidently.

What We're Looking For?

• 5+ years in software quality engineering or test automation.

• Strong API and backend testing experience, including asynchronous and integration-heavy systems.

• Experience testing mobile and web applications and understanding client/ server failure modes.

• Ability to write automation in JavaScript/ TypeScript, Python, Java, or a similar language.

• Strong debugging skills across logs, network requests, databases, and distributed services.

• Experience with CI/CD and integrating automated tests into release pipelines.

• A product mindset: prioritize risk and customer impact rather than maximizing test-case counts.

Nice to Have

• Performance, load, security, or reliability testing.

• Experience with Playwright, Cypress, Appium, Postman/ Newman, k6, or similar tooling.

• Experience with event-driven systems, queues, webhooks, and long running workflows.

• Experience testing AI-assisted or non-deterministic product behavior.

How We Think About Quality?

Quality is an engineering responsibility. Automation should create confidence, not dashboards. A production escape should improve the system that allowed it to happen. The goal is simple: ship quickly without making customers our test environment.

Job Description

We are looking for an experienced Data Engineer with strong expertise in Python, ETL, SQL, CI/CD, and DevOps to design, develop, and maintain scalable data pipelines and data processing solutions.

Key Responsibilities

• Design, develop, and maintain scalable ETL/ELT data pipelines.
• Develop data processing solutions using Python.
• Write complex and optimized SQL queries, stored procedures, and data transformations.
• Build and maintain data ingestion and integration workflows.
• Implement data quality, validation, monitoring, and error-handling processes.
• Develop and maintain CI/CD pipelines for data engineering applications.
• Work with DevOps tools and practices for automated build, deployment, and infrastructure management.
• Collaborate with data analysts, data scientists, software engineers, and business teams.
• Optimize data pipelines for performance, reliability, and scalability.
• Troubleshoot production data issues and ensure timely resolution.
• Follow best practices for version control, code quality, testing, and deployment.

Mandatory Skills

• Python
• ETL
• SQL
• CI/CD
• DevOps
• Git / Version Control
• Strong problem-solving and debugging skills

Job Title : Data / AI / GenAI – Engineering & Analytics

Experience : 4+ Years

Location : Noida / Gurugram / Ahmedabad

Employment Type : Full-time | On-site at client location

Working Days : 5 days per week

Working Hours : Standard business hours

Position Overview : We are seeking professionals to deliver modern data engineering, business intelligence, cloud analytics and AI-powered applications, according to their specialization.

Mandatory Skills :

Python, SQL, ETL/ELT, Data Engineering, Power BI, Azure Data Factory, Databricks, PySpark, Data Modeling, GenAI/LLMs, RAG, Vector Databases, AI Agents (as per role specialization).

Key Roles / Specializations :

1. Power BI Developers : Dashboards, DAX, Power Query, reporting and data modeling
2. Azure Data Engineers : Azure Data Factory, Data Lake, Azure SQL and cloud pipelines
3. Databricks Engineers : Apache Spark, PySpark, Delta Lake and scalable processing
4. Data Engineers : ETL/ELT, SQL, Python, data warehousing and quality
5. GenAI / RAG Engineers : LLMs, prompts, embeddings, vector databases and retrieval pipelines
6. Agentic AI Engineers : AI agents, tool calling, orchestration and multi-agent workflows

Key Responsibilities :

• Design, develop and maintain data pipelines, analytics solutions or AI applications.
• Build and optimize data integration, transformation and processing workflows.
• Develop dashboards and analytical models for business decision-making.
• Use cloud data platforms and modern engineering frameworks.
• Develop and evaluate LLM applications, RAG solutions or AI agents as applicable.
• Ensure data quality, security, performance and reliability.
• Collaborate with engineering teams and stakeholders on testing, deployment and documentation.

Required Skills & Qualifications :

• Bachelor’s degree in Computer Science, IT, Data Science, Engineering or related discipline.
• 4–5 years of relevant experience in data, analytics, AI or software engineering.
• Hands-on expertise in at least one listed specialization; not all technologies are required.
• Relevant Python, SQL, DAX or other technical skills depending on the position.
• Understanding of cloud platforms, APIs, integration and software practices.

Preferred Qualifications :

• Azure, Databricks or Microsoft Fabric experience.
• For GenAI roles : Azure OpenAI, OpenAI APIs, LangChain, LlamaIndex or LangGraph.
• For relevant roles : vector databases, CI/CD, Docker, MLOps or LLMOps.

Note : Candidates are expected to have expertise in their relevant specialization, not in every listed technology or role.