Data Quality Engineer

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

Experience                    : 5+ years

Work type                      : Chennai - Work from Office/ Other Locations - Remote

Employment Type      : Full Time

Notice Period               : Immediate

Work Day                       :Mon to Fri

Key Responsibilities:

• Ingestion pipelines: Confluence, SharePoint/Microsoft 365 (Graph), and repository connectors — parsing, chunking, metadata, incremental sync, data-quality controls
• Synthetic and non-production data design: corpora shaped to banking IT content (runbooks, incidents, KB articles, change records) with realistic permission structures — the foundation of the cloud-first build
• The evaluation harness as a product: golden question sets, retrieval precision/faithfulness/citation-accuracy scoring, the zero-leakage permission suite, the zero-unauthorized-actions agent suite; CI-integrated regression gates
• Performance and load testing with the platform engineer: concurrency profiles, soak tests, degraded-mode behavior
• UAT orchestration and defect triage across both use cases; acceptance evidence packs per milestone
• Measurement reporting foundations: the before/after value metrics (time saved per incident, per search) the client's executives receive monthly

Technical Skills:

• 5+ years across data engineering and quality engineering with production Python; you have built pipelines AND the tests that police them
• LLM evaluation experience: has designed or operated retrieval/generation quality measurement with numeric thresholds (RAGAS-class metrics, custom harnesses, or equivalent) — not just eyeballed outputs
• Document-processing depth: parsing real enterprise content (tables, permissions, versions, mess), chunking trade-offs, metadata design

• Test-suite craftsmanship: negative and adversarial test design — the leakage suite is a security artifact, and you think like an attacker when writing it
• Load/performance testing experience (Locust, k6, or equivalent) and defect-triage discipline

Strongly Preferred :

Synthetic-data generation for regulated domains; Microsoft Graph and Confluence APIs; Milvus/pgvector; Splunk data onboarding; UAT facilitation with business users; banking data-handling standards

About Ampera: 

Ampera Technologies, a purpose driven Digital IT Services with primary focus on supporting our client with their Data, AI / ML, Accessibility and other Digital IT needs. We also ensure that equal opportunities are provided to Persons with Disabilities Talent. Ampera Technologies has its Global Headquarters in Chicago, USA and its Global Delivery Center is based out of Chennai, India. We are actively expanding our Tech Delivery team in Chennai and across India. We offer exciting benefits for our teams, such as 1) Hybrid and Remote work options available, 2) Opportunity to work directly with our Global Enterprise Clients, 3) Opportunity to learn and implement evolving Technologies, 4) Comprehensive healthcare, and 5) Conducive environment for Persons with Disability Talent meeting Physical and Digital Accessibility standards. 

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 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

Job Summary

Role Overview

We are looking for an experienced Data Engineer with strong expertise in Python, ETL, Advanced SQL, CI/CD, DevOps, and Data Analytics. The ideal candidate should have hands-on experience designing and developing scalable data pipelines, transforming large datasets, and supporting data-driven applications.

Experience with Google Cloud Platform (GCP) will be an added advantage.

Key Responsibilities

• Design, develop, and maintain scalable ETL/ELT data pipelines using Python and SQL.
• Develop complex and optimized SQL queries, stored procedures, and data transformations.
• Build and maintain reliable data integration workflows across multiple data sources.
• Perform data cleansing, validation, transformation, and quality checks.
• Analyze data and provide insights to support business and technical requirements.
• Implement and maintain CI/CD pipelines for data engineering applications.
• Work with DevOps practices and tools to automate deployments, monitoring, and infrastructure processes.
• Troubleshoot data pipeline failures, performance issues, and production incidents.
• Optimize data processing workflows for performance, scalability, and reliability.
• Collaborate with Data Analysts, Data Scientists, Developers, and other stakeholders.
• Follow best practices for version control, testing, documentation, and deployment.
• Contribute to cloud-based data engineering initiatives, preferably on GCP.

Required Skills

• 5–7 years of hands-on experience in Data Engineering.
• Strong programming skills in Python.
• Strong expertise in Advanced SQL and database concepts.
• Hands-on experience with ETL/ELT processes and data pipelines.
• Good understanding of Data Warehousing and Data Modeling concepts.
• Experience with CI/CD practices and tools.
• Strong understanding of DevOps principles, automation, and deployment processes.
• Strong data analytics and problem-solving skills.
• Experience working with large datasets and performance optimization.
• Good understanding of Git/version control and software development best practices.

Good to Have

• Hands-on experience with Google Cloud Platform (GCP).
• Exposure to GCP data services such as BigQuery, Cloud Storage, Dataflow, Composer, or Pub/Sub.
• Experience with containerization/orchestration technologies such as Docker/Kubernetes.
• Experience with workflow orchestration tools such as Airflow.
• Knowledge of cloud-based data architecture and distributed data processing.

Preferred Candidate Profile

• Strong analytical and problem-solving abilities.
• Good communication and stakeholder management skills.
• Ability to work independently as well as in a collaborative team environment.
• Strong ownership of data pipelines and production systems.
• Candidates who can join at short notice are preferred.

Mandatory Skills

 Data Engineer, Python , ETL, GCP, Advanced SQL, Strong Data Analytics skills, CICD, Devops

We are looking for a dynamic Data Engineer to join our team of technology enthusiasts. You will leverage data to drive strategic decision-making and pioneering solutions, working with complex datasets, collaborating closely with stakeholders, and transforming data into actionable insights to drive innovation.

Qualifications and Skills:

• Minimum 5 years of experience as a Data Engineer
• Hands-on experience with Azure cloud-based data solutions
• Expertise in database design and management, including SQL databases such as SQL Server
• Proficient in ETL (Extract, Transform, Load) design for data integration and processing
• Strong knowledge of data modeling principles and techniques
• Ability to analyze and translate data into actionable insights, reports, and visualizations
• Proficiency in Power BI for reporting and data visualization

Desirable Skills:

• Experience with Power BI Report Builder / Reporting Services
• Knowledge of statistical analysis or Data Science
• Experience within the UK Insurance industry is a plus
• Python or R coding skills

Responsibilities:

• Implement efficient data exchange between internal and external systems to increase efficiency and reduce re-keying and translation errors
• Support the Broking business by developing high-quality information resources, ensuring data availability and accessibility for decision-making
• Engineer data inputs and outputs from core applications and semi-structured remote service data through data syncs between data lake, ODS (SQL database), and leveraging Fabric and ADF
• Perform data engineering tasks including ingestion, cleansing, and collation from a wide range of internal and external sources
• Implement different methods of streaming data and create reconciliations for datasets
• Build analytical models to support reporting and analytics
• Collaborate with an agile delivery team to work on the backlog of specified work

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.