Senior Data Engineer Data Engineering • Full-time, Onsite • Bangalore / Chennai / Kochi (Work from Office) Exp: 4-6 years experience About the Role We are looking for a Senior Data Engineer to design, build, and operate the data pipelines and lakehouse platform that power analytics and data products across the business. You will own end-to-end ingestion, transformation, and modeling on Databricks and Microsoft Fabric - turning raw, heterogeneous source data into reliable, well-governed, analytics-ready datasets. This is a hands-on senior individual-contributor role. Beyond writing production-grade pipelines, you will set engineering standards, review designs, and mentor mid-level engineers on the team. The role is industry-agnostic — you will work across a range of data domains and source systems. What You'll Do Build & operate pipelines

- Design and maintain scalable batch and streaming data pipelines (ELT/ETL) on Databricks, ingesting from databases, files, APIs, and event streams. Lakehouse & modeling

- Architect and implement a medallion (bronze/silver/gold) lakehouse on Delta Lake; design dimensional and analytics-ready data models for downstream consumption. Microsoft Fabric delivery

- Deliver data into and across Microsoft Fabric (Lakehouse, Warehouse, OneLake, Pipelines/Dataflows) and enable BI and semantic-model consumption. Orchestration & reliability

- Orchestrate workflows with Airflow and/or Azure Data Factory; build in data-quality checks, monitoring, alerting, and SLAs. Governance

- Implement cataloging, lineage, and access controls using Unity Catalog and Microsoft Purview. Performance & cost

- Tune Spark jobs, storage layout, and cluster configuration for performance and cost efficiency. Standards & mentorship

- Define engineering best practices, conduct design and code reviews, and mentor mid-level data engineers.

What We're Looking For 4–6 years of professional data engineering experience building and operating production data pipelines.



Strong hands-on experience with

Databricks

- Spark (PySpark/Spark SQL), Delta Lake, notebooks/jobs, and cluster management. Proven experience designing and building

data pipelines

(batch and streaming) at scale, with a solid grasp of ELT/ETL patterns. Experience with

Microsoft Fabric

- Lakehouse, Warehouse, OneLake, and Fabric Pipelines/Dataflows. Strong data modeling skills - medallion/lakehouse architecture and dimensional modeling. Proficiency in

Python

and advanced

SQL . Experience with workflow orchestration ( Airflow

and/or

Azure Data Factory ). Experience with data governance tooling ( Unity Catalog

and/or

Microsoft Purview ). Experience with streaming ingestion ( Kafka / Event Hubs

and Spark Structured Streaming). Ability to work independently, set technical direction, and mentor others.

Nice to Have AWS data experience

- S3, Glue, Redshift, EMR, Athena, or Lake Formation (a strong plus).

Infrastructure-as-code and CI/CD for data (Terraform, Git-based deployment, automated testing). Experience with dbt for transformation and testing. Familiarity with Power BI semantic models and BI enablement. Databricks or Microsoft (Azure) certifications.

Technology Stack Databricks:

Apache Spark (PySpark, Spark SQL), Delta Lake, Databricks Workflows/Jobs, Unity Catalog, Delta Live Tables. Microsoft / Fabric:

Microsoft Fabric (Lakehouse, Warehouse, OneLake, Pipelines, Dataflows Gen2), Azure Data Factory, Azure Data Lake Storage, Microsoft Purview, Power BI. Pipelines & Orchestration:

Apache Airflow, Azure Data Factory, Kafka / Azure Event Hubs, Spark Structured Streaming. Languages & Tooling:

Python, SQL, Git, CI/CD, Terraform, dbt. AWS (plus):

S3, AWS Glue, Amazon Redshift, EMR, Athena, Lake Formation. Why Join Us You'll take real ownership of a contemporary lakehouse platform, work across a broad set of data domains, and shape how the team builds data. We value skills and impact over formal credentials — there is no degree or certification requirement for this role.

📌 Senior Data Engineer (Mumbai)
🏢 Xencia Technology Solutions
📍 Mumbai