Azure Data Engineer at Everforth Quinnox · Bengaluru (Bangalore), Mumbai · 7 - 10 years · ₹20L - ₹25L / yr (ESOP available) · Profitable · Posted 12 May 2026

Azure Database Developer
Mandatory Skills: Data Bricks (Pyspark/Spark), Unity Catalog, T-SQL, Azure Data Factory, Power BI.
Power BI, & Azure Devops
· Very strong understanding on ETL and ELT
· Very strong understanding on Medallion architecture.
· Very strong knowledge in Pyspark and Spark architecture.
· Very strong knowledge in Unity Catalog architecture using databricks.
· Very strong knowledge in T-SQL
· Good knowledge in Azure data lake architecture and access controls.
· Good knowledge in data pipeline creation and monitoring using Azure data factory
· Good knowledge in CI /CD process using Azure devops
· Power BI

Similar jobs (10)
8-12 years experience on Data Engineering role working with Databricks & Azure Cloud technologies.
• Bachelor’s degree in computer science, Information Technology, or related field.
• Strong proficiency in PySpark, Python, SQL.
• Strong experience in data modeling, ETL/ELT pipeline development, and automation • Hands-on experience with performance tuning of data pipelines and workflow
• Proficient in working on Azure cloud components Azure Data Factory, Azure DataBricks, Azure Data Lake etc.
• Experience with data modeling, ETL processes, Delta Lake and data warehousing.
• Experience on Delta Live Tables, Autoloader & Unity Catalog.
Preferred - Knowledge of the insurance industry and its data requirements.
• Strong analytical skills with the ability to collect, organize, analyze, and disseminate significant amounts of information with attention to detail and accuracy.
• Excellent communication and problem-solving skills to work effectively with diverse teams
• Excellent problem-solving skills and ability to work under tight deadlines.
Solution Architect – AZURE Data Engineering
Job Overview
We are looking for an experienced Solution Architect – Data Engineering with strong expertise in designing data solutions and hands-on experience with Azure, Synapse, PySpark, Data Warehousing, and Data Lakes. The ideal candidate should have strong architectural and data engineering knowledge.
Key Responsibilities
- Design and implement scalable data architecture and solutions.
- Develop and manage Data Warehouse and Data Lake architectures.
- Design data platforms using Medallion Architecture.
- Lead Data Engineering and ETL activities.
- Work with Azure Synapse Analytics for data processing and analytics.
- Develop data solutions using PySpark / Apache Spark.
- Define and implement data validation and data quality processes.
- Collaborate with business, data, and technology teams to deliver effective data solutions.
Required Skills
- Strong experience in Solution Architecture / Data Architecture.
- Strong knowledge of Data Warehouse and Data Lake architecture.
- Good understanding of Medallion Architecture.
- Strong experience in Data Engineering and ETL.
- Hands-on experience with Microsoft Azure and Azure Synapse Analytics.
- Strong knowledge of PySpark / Apache Spark.
- Experience with Data Validation and Data Quality.
- Good communication and stakeholder management skills.
Experience
8+ Years
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
Data Architect – Databricks & AWS
- Strong experience in Data Architecture, Data Engineering, Databricks, Apache Spark/PySpark, Python, and Advanced SQL.
- Design and implement scalable ETL/ELT pipelines, data platforms, and Lakehouse architectures using Medallion Architecture.
- Experience with Databricks, Databricks Workflows, Unity Catalog OR Databricks Jobs
- Strong knowledge of Delta Lake, Databricks Workflows, Delta Live Tables (DLT), and dimensional data modeling.
- Hands-on experience with AWS services such as S3, Glue, IAM, Lambda, and CloudWatch.
- Experience with Apache Airflow, Data Warehouse concepts, Git/CI-CD, performance optimization, and data quality.
- Good to have exposure to Kafka/Structured Streaming, Unity Catalog, and modern data governance.
Technical Lead
Job Description
Role Overview
We are seeking a highly skilled Data Engineering Lead with minimum of 5 years of hands-on experience in Azure data engineering, data warehousing, and automation-driven integration. The ideal candidate should be a proven technical lead, capable of driving end-to-end
project delivery and working closely with customer teams. This is a Work from Office / Customer Site role.
Roles and Responsibilities
• Lead the design, development, and delivery of data engineering and automation projects.
• Architect and implement ETL/ELT pipelines using Azure Data Factory.
• Design and manage enterprise data warehouses including dimensional modeling and
schema optimization.
• Manage Azure components including Storage Accounts, Data Lakes, Azure SQL, and Synapse.
• Drive automation initiatives across data ingestion and transformation workflows.
• Collaborate with business and technical stakeholders to translate requirements into scalable solutions.
• Mentor team members and enforce engineering best practices.
• Serve as the technical anchor responsible for ensuring high-quality, on-time delivery.
Skills and Qualification
• Strong hands-on experience with Azure Data Factory, Azure Storage, Azure SQL/Synapse.
• Deep understanding of data warehousing concepts: star/snowflake schemas, fact/dimension modeling.
• Experience with automation-led data engineering solutions.
• Strong troubleshooting, optimization, and analytical skills.
• Excellent communication and stakeholder management abilities.
• Proven experience as a Technical Lead leading teams and delivery.
Must Have
• Min of 5 years of relevant data engineering experience.
• Strong Azure Data Engineering and Data Warehousing expertise.
• Proven Technical Lead experience.
• Ability to work from office and customer site.
• Strong ownership mindset with a focus on quality and delivery excellence.
Role Descriptions: Azure data engineer
SN Required Information Details
1 Role** Azure Cosmos DB Developer
2 Required Technical Skill Set** Primary - PySpark Azure Cosmos DB
Secondary -Python, Microsoft Fabric
3 No of Requirements** 4
4 Desired Experience Range** 8 to 12
5 Location of Requirement Pune
Desired Competencies (Technical/Behavioral Competency)
Must-Have**
1. Deep hands-on experience with Python,Pyspark,Spark batch,notebook in Azure
2. Experience in Cosmos DB – including data modeling, indexing, partitioning, consistency levels, and performance tuning.
3. Strong understanding of Cosmos DB APIs (Core SQL API, MongoDB API, etc.) and integration patterns.
4. Proficiency in query optimization and troubleshooting Cosmos DB performance issues.
5. Experience in data processing using PySpark and Python.
6. Familiarity with Microsoft Fabric for data engineering and analytics workflows.
7. Proficient using source code management tools such as Git or GitHub
8. Experience with Test Driven Development and / or Behavior Driven Development.
Good-to-Have 1. Exposure to data governance tools like Azure Purview.
2. Familiar with various design patterns
3. Familiar with Azure: SQL Managed Instance, Cosmos DB, Storage Services, Azure Functions
4. Global project experience, and excellent communication skills, verbal and written, and soft skills in agile projects
SN Responsibility of / Expectations from the Role
1 Design and implement scalable and high-performance solutions using Azure Cosmos DB.
2 Develop data ingestion and transformation pipelines using PySpark and Azure Data Factory.
3 Optimize Cosmos DB performance through indexing, partitioning, and query tuning.
4 Collaborate with architects and data engineers to ensure best practices in data modeling and cloud architecture.
5 Implement and maintain CI/CD pipelines for automated deployments and testing.
6 Troubleshoot and resolve technical issues related to Cosmos DB and data pipelines.
Desirable Skills:
Keyword:
Skills: Digital : Python~Digital : Databricks~Digital : PySpark~Microsoft Fabric~MySQL
Experience Required: 8-10.
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
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.
Data Engineer – Microsoft Fabric
Location: Pune, India
Work Mode: Hybrid
Experience: 6+ Years
Employment Type: Full-time contactor
Compensation: As per market standards, commensurate with experience and expertise
Shift Timings: 2:00 PM – 11:00 PM IST
Notice Period: 0 – 15 days
About the Role
Jade Business Services (JBS) is seeking a Data Engineer – Microsoft Fabric to join our Pune team and work on enterprise-scale data transformation and analytics initiatives.
We are looking for a hands-on Data Engineer with strong experience in Microsoft Fabric, SQL, Python/PySpark and modern data engineering practices. The candidate will be responsible for building scalable data pipelines, implementing Lakehouse and Warehouse solutions, developing data models and supporting governed, reliable and AI-ready data platforms.
The ideal candidate should be comfortable working with architects, engineering teams and client stakeholders to translate business requirements into scalable and production-ready data solutions.
Roles and Responsibilities
- Design and develop data solutions using Microsoft Fabric, including OneLake, Lakehouse, Warehouse and Data Factory pipelines.
- Build and maintain scalable ETL/ELT pipelines for batch and incremental data processing.
- Develop data ingestion and transformation pipelines using Fabric Data Factory, SQL, Python and/or PySpark.
- Implement Medallion Architecture using Bronze, Silver and Gold layers.
- Work with Lakehouse and Fabric Warehouse for enterprise data processing and analytics.
- Develop and maintain data models, tables, views and optimized SQL queries.
- Build and support semantic models for Power BI and analytical workloads.
- Implement data quality, validation, monitoring and error-handling mechanisms.
- Work with metadata, lineage and governance requirements using Microsoft Purview.
- Implement data security, access controls and role-based permissions across data platforms.
- Support Data Product and domain-oriented data architecture principles.
- Follow DataOps practices including CI/CD, deployment, monitoring and production support.
- Troubleshoot pipeline failures, performance issues and data quality problems.
- Optimize data pipelines, queries and storage for performance and cost efficiency.
- Work closely with Data Architects and business stakeholders to understand requirements and implement technical solutions.
- Participate in technical design discussions, code reviews and architecture reviews.
- Maintain technical documentation, data flow diagrams and pipeline documentation.
- Support production deployments, incident resolution and SLA-driven data platform operations.
- Identify opportunities for automation and AI-assisted improvements across data engineering processes.
Qualifications and Skills
- 6+ years of experience in Data Engineering, Data Integration or Data Platform development.
- Strong hands-on experience with Microsoft Fabric.
- Experience with:
- Microsoft Fabric Lakehouse
- Fabric Warehouse
- OneLake
- Fabric Data Factory / Pipelines
- Semantic Models
- Strong understanding of Lakehouse and Medallion Architecture.
- Strong SQL development and query optimization skills.
- Hands-on experience with Python and/or PySpark.
- Experience developing enterprise ETL/ELT and data integration pipelines.
- Experience with batch and incremental data processing.
- Understanding of data modelling concepts including dimensional modelling.
- Knowledge of data quality, metadata, lineage and data governance.
- Working knowledge of Microsoft Purview.
- Understanding of Data Mesh and Data Product concepts.
- Experience with CI/CD, version control, monitoring and DataOps practices.
- Understanding of cloud security, access controls and data privacy.
- Good troubleshooting and problem-solving skills.
- Strong communication skills and ability to work with distributed and client-facing teams.
Preferred Skills
- Microsoft Fabric or Azure Data certifications.
- Experience migrating workloads from Azure Synapse, SQL Server, Databricks or other data platforms to Microsoft Fabric.
- Experience implementing Medallion Architecture on Microsoft Fabric.
- Experience with Power BI and semantic modelling.
- Exposure to AI/ML, Generative AI or Agentic AI use cases on enterprise data platforms.
- Experience working with Data Products or domain-oriented data solutions.
- Experience in Energy & Utilities, Healthcare, Financial Services or Insurance.
- Experience working with US or international enterprise clients.
What We Expect
The ideal candidate should be hands-on first and capable of independently building, troubleshooting and optimizing Fabric data solutions. You should be able to explain the technical decisions behind your implementation and work effectively with architects and engineering teams to deliver production-ready solutions.
The recruiter has not been active on this job recently. You may apply but please expect a delayed response.
Job Summary
The Technical Lead will be responsible for overseeing and leading projects related to Azure Data Factory (ADF), Azure Databricks, SQL, Oracle PL/SQL, and Python. The role involves designing, developing, and implementing data solutions while ensuring they meet the business requirements and align with best practices. (1.) Key Responsibilities
1. Lead and manage end-to-end data engineering projects using azure data factory, azure databricks, sql, oracle pl/sql, and python.
2. Collaborate with stakeholders to gather and understand requirements for data pipelines and analytics solutions.
3. Design and develop etl processes, data models, and data integration solutions.
4. Provide technical guidance and mentorship to the team members.
5. Ensure data quality, data governance, and data security standards are maintained throughout the project lifecycle.
6. Troubleshoot and optimize data pipelines and processes for performance and efficiency.
7. Stay updated on the latest trends and technologies in data engineering and contribute to continuous improvement efforts.
Skill Requirements
1. Proficiency in azure data factory (adf) and azure databricks for building and managing data pipelines.
2. Strong experience with sql and oracle pl/sql for data querying and manipulation.
3. Advanced programming skills in python for scripting and data processing tasks.
4. Knowledge of data modeling, data warehousing concepts, and database design principles.
5. Ability to work in a collaborative team environment and communicate effectively with stakeholders.
6. Strong analytical and problem-solving skills with attention to detail.
7. Experience in data visualization tools and techniques is a plus.
Certifications: Relevant certifications in Azure Data Factory, Azure Databricks, SQL, Oracle PL/SQL, or Python are advantageous.
Skill (Primary)
Data Fabric-Azure-Azure Data Factory (ADF)













