Posted on: 17/06/2026
JOB DESCRIPTION :
Role : Senior Data Engineer
Data & Analytics Engineering
About the Role :
We are looking for a Senior Data Engineer to join our growing Data & Analytics team. In this role, you will design, build, and maintain scalable data pipelines and platforms that power critical business decisions. You will be a key contributor in driving our cloud-first data strategy, leveraging Azure Databricks as a core technology and Azure Data Factory (ADF) as a good to have feature. You will collaborate closely with data scientists, analysts, and product teams to deliver high-quality, reliable, and performant data solutions in a fast-paced environment.
Key Responsibilities :
Data Pipeline & Architecture :
- Design, develop, and maintain robust ETL/ELT pipelines using Azure Databricks and Azure Data Factory (ADF).
- Architect and implement scalable data lakehouse solutions on Azure using Delta Lake.
- Build and optimize data workflows across batch and streaming workloads (Spark Structured Streaming, Event Hubs).
- Define and enforce data modeling best practices (star schema, data vault, medallion architecture).
Databricks Engineering :
- Develop and optimize Spark-based data transformations using PySpark and Spark SQL in Databricks.
- Manage Databricks clusters, jobs, and workspace configurations for performance and cost efficiency.
- Implement Delta Live Tables (DLT) pipelines for declarative, auto-scaling data transformations.
- Leverage Unity Catalog for data governance, lineage tracking, and access control.
- Utilize Databricks Asset Bundles (DABs) and CI/CD practices for deployment automation.
Azure Data Factory (ADF) (Good To Have Feature) :
- Build, schedule, and monitor complex ADF pipelines with parameterized templates.
- Integrate ADF with Azure Key Vault, Linked Services, and Integration Runtimes (SHIR/Azure IR).
- Implement incremental load patterns, watermarking, and change data capture (CDC) strategies.
- Troubleshoot pipeline failures and optimize ADF pipeline performance and cost.
Data Quality & Governance :
- Implement data quality frameworks and validation checks across pipelines.
- Enforce data cataloging, lineage, and metadata management practices.
- Collaborate with data governance teams to ensure compliance with data policies and regulations (GDPR, HIPAA).
Collaboration & Leadership :
- Mentor junior data engineers and conduct code reviews.
- Work closely with data scientists and ML engineers to productionize machine learning models.
- Partner with DevOps/Cloud teams on infrastructure-as-code (Terraform/Bicep) for data platform provisioning.
- Document architecture decisions, pipeline designs, and operational runbooks.
Required Qualifications :
- 7+ years of hands-on experience with Azure Databricks (Spark SQL, Delta Lake, PySpark).
- Strong proficiency in SQL preferred and Python.
- Deep understanding of distributed computing principles and the Apache Spark ecosystem.
- Experience with Azure data services : ADLS Gen2, Azure Synapse, Azure SQL, Event Hubs / Kafka.
- Solid understanding of data warehousing concepts and dimensional modeling.
- Experience with version control (Git) and CI/CD tools (Azure DevOps, GitHub Actions).
- Familiarity with infrastructure-as-code tools (Terraform or ARM/Bicep).
Preferred Qualifications :
- Databricks Certified Data Engineer Associate or Professional certification.
- Microsoft Certified : Azure Data Engineer Associate (DP-203).
- Experience with Delta Live Tables (DLT) and Databricks Workflows.
- Familiarity with Power BI or other BI/reporting tools.
- Experience with Scala or Java for Spark development.
Technology Stack :
Core Platforms :
- Azure Databricks (Preferred), Azure Data Factory (ADF) (Good to have)
Data Storage :
- Azure Data Lake Storage Gen2, Delta Lake, Azure SQL, Cosmos DB
Languages :
- Python (PySpark), SQL
Orchestration :
- ADF Triggers, Databricks Workflows, Apache Airflow
Monitoring :
- Azure Monitor, Log Analytics, Databricks Cluster Policies
Governance :
- Unity Catalog, Azure Purview, Azure Key Vault (Good to have)
BI / Reporting :
- Power BI, Tableau
Key Competencies :
- Strong analytical and problem-solving skills with attention to detail.
- Excellent communication skills - ability to translate complex technical concepts to non-technical stakeholders.
- Self-motivated and able to manage competing priorities in an agile environment.
- Collaborative team player with a growth mindset and eagerness to mentor others.
- Proactive in identifying performance bottlenecks and proposing architectural improvements.
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Recruiter
HR at CONCORD GLOBAL IT SERVICES LLP
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Posted in
Data Engineering
Functional Area
Data Engineering
Job Code
1645745