Data Engineer at Upboot Consulting Services · Remote only · 5 - 8 years · ₹7L - ₹12L / yr · Raised funding · Remote only · Posted 31 Dec 2021

Mandate skills set: Azure and Python with Data Framework
Experience: 5-8yrs
Package : 1Lakh per month
Mode: C2H (6months-1year)

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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 :
- Power BI Developers : Dashboards, DAX, Power Query, reporting and data modeling
- Azure Data Engineers : Azure Data Factory, Data Lake, Azure SQL and cloud pipelines
- Databricks Engineers : Apache Spark, PySpark, Delta Lake and scalable processing
- Data Engineers : ETL/ELT, SQL, Python, data warehousing and quality
- GenAI / RAG Engineers : LLMs, prompts, embeddings, vector databases and retrieval pipelines
- 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.
Location: Bangalore Experience: 5 to 7 years Employment type: Full-time, permanent Work Hours: General Shift (10.00 AM to 7.00 PM) website: www.amazech.com Qualifications: Minimum B.E./B.Tech, or higher in Computer Science, Information Technology, Data Engineering, or a related field, with a good academic background. Key Responsibilities: • Design, develop, and maintain end-to-end data pipelines. • Build and optimize ETL/ELT processes for large-scale data processing. • Implement Azure-based data solutions ensuring scalability and performance. • Collaborate with stakeholders to understand business data requirements. • Perform performance tuning and optimization across data platforms. • Support production environments, conduct root cause analysis, and resolve data-related issues. • Maintain comprehensive technical documentation and structured knowledge transfer documents. • Work effectively within Agile/Scrum frameworks and contribute to sprint planning and delivery. • Ensure secure and compliant data handling using Azure best practices. Required Skills & Experience • End-to-end ETL/ELT pipeline development, integration, and performance optimization • Azure Synapse, Azure Logic Apps, Azure SQL, and Azure Databricks, with a strong focus on performance tuning • Microsoft Azure services, including Storage Accounts, Key Vault, and Cognitive Services • Advanced proficiency in Python development and modern productivity tools such as GitHub Copilot and Cursor • Strong documentation discipline, including technical design documentation, and structured knowledge transfer documents • Experience operating within Agile/Scrum frameworks, including production support, root cause analysis, and effective stakeholder collaboration
Job Description – Data Engineer
Role: Data Engineer
Experience: 9+ Years
Location: Bangalore / Hyderabad
Notice Period: Immediate to 15 Days
Interview Process: 1st Round – Virtual | 2nd Round – F2F
Mandatory Skills
- Python
- PySpark
- SQL
- Azure Data Engineering
Job Description
We are looking for an experienced Azure Data Engineer with 9+ years of experience and strong hands-on expertise in Python, PySpark, SQL, and Azure Data Engineering.
Key Responsibilities
- Develop and maintain scalable data engineering solutions using Azure.
- Build and optimize data processing pipelines using PySpark and Python.
- Write complex SQL queries for data extraction and transformation.
- Work with Azure data services and cloud-based data platforms.
- Perform data processing, transformation, and integration.
- Troubleshoot data pipeline and production issues.
- Collaborate with technical and business teams to deliver data solutions.
Preferred: Immediate to 15 Days joiners.
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
We are looking for a skilled and experienced Data Engineer to join our growing data team. The ideal candidate will have strong expertise in Python, PySpark, Data Modeling, and Power BI, with hands-on experience in designing, developing, and optimizing scalable data solutions. The role requires working closely with business stakeholders, data architects, and analytics teams to build robust data pipelines and semantic models that enable data-driven decision-making.
Technical Skills
- Strong hands-on experience in Python and PySpark development.
- Expertise in building and optimizing Data Engineering solutions and ETL pipelines.
- Strong understanding of Data Modeling concepts (Star Schema, Snowflake Schema, Dimensional Modeling).
- Experience with Power BI Data Modeling and Semantic Layer development.
- Proficiency in DAX (Data Analysis Expressions).
- Experience designing and managing Semantic Models in Power BI.
- Strong SQL skills and experience working with large datasets.
- Knowledge of data warehousing concepts and best practices.
Preferred Skills
- Experience with cloud platforms such as Azure, AWS, or GCP.
- Exposure to modern data platforms like Databricks.
- Understanding of data governance and data quality frameworks.
Job Description – Senior GCP Data Engineer
Position: Senior GCP Data Engineer
Experience: 8+ Years
Budget: Up to 30 LPA
Location: Bangalore / Hyderabad
Relocation: Candidates from Chennai / Pune willing to relocate are also welcome.
Notice Period: Immediate to 15 Days
Interview Process:
- Round 1: Virtual Interview
- Round 2 / DM Round: Face-to-Face Interview
Required Skills
- Strong hands-on experience in GCP Data Engineering.
- Good programming experience in Python.
- Strong experience with PySpark / Apache Spark.
- Proficiency in SQL and database concepts.
- Experience in developing and maintaining data pipelines.
- Good understanding of data processing, transformation, and integration.
- Experience in handling large-scale data processing.
- Strong problem-solving and debugging skills.
- Good understanding of cloud-based data engineering concepts.
- Experience in optimizing data pipelines for performance and scalability.
Preferred Skills
- Previous experience in a Lead Data Engineer role.
- Experience in technical leadership, mentoring, and guiding team members.
- Ability to collaborate with cross-functional teams and deliver data engineering solutions.
Roles & Responsibilities
- Design, develop, and maintain scalable data pipelines using GCP.
- Develop data processing and transformation workflows using Python and PySpark.
- Write and optimize SQL queries for efficient data processing.
- Build and maintain reliable data engineering solutions.
- Troubleshoot data pipeline issues and optimize performance.
- Ensure data quality, reliability, and scalability.
- Collaborate with stakeholders and team members to deliver project requirements.
- Lead and guide team members where applicable.
- Important: Candidates must have strong Senior Data Engineer experience. Lead experience is preferred but not mandatory.
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.
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 Description
We are looking for an experienced Azure Synapse Data Engineer with strong hands-on expertise in Azure data engineering, data warehousing, ETL/ELT, and SQL performance optimization.
Key Responsibilities
- Design, develop, and optimize solutions using Azure Synapse Analytics.
- Build and maintain data integration pipelines using Azure Data Factory (ADF) and Synapse Pipelines.
- Design and implement scalable Azure Data Lake Storage Gen2 (ADLS Gen2) architectures.
- Develop robust and high-performance ETL/ELT frameworks for enterprise data platforms.
- Monitor and troubleshoot large-scale data ingestion, transformation, and processing workloads.
- Identify and resolve performance bottlenecks across data movement and transformation processes.
- Ensure data quality, availability, reliability, and consistency across analytics platforms.
- Perform advanced SQL query analysis and optimization.
- Analyze execution plans and optimize complex analytical workloads.
- Configure and tune Synapse Dedicated SQL Pools.
- Design efficient partitioning strategies for large datasets.
- Optimize indexing, statistics, and workload distribution to improve query performance.
Mandatory Skills
- Azure Synapse Analytics
- Azure Data Factory (ADF)
- Synapse Pipelines
- ADLS Gen2
- ETL/ELT
- Strong SQL
- Synapse Dedicated SQL Pool
- SQL query/execution plan optimization
- Partitioning, indexing, and statistics
- Azure data warehouse / data lake architecture
- Performance tuning and troubleshooting
Ideal Candidate
A strong Azure Data Engineer with hands-on experience in Synapse + ADF + ADLS Gen2 + Advanced SQL + Dedicated SQL Pool performance tuning.
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













