Senior Data Engineer

Xencia Technology Solutions; Ernakulam, Bengaluru; On-site; INR 4,500,000 - 6,000,000; Full time

Job summary

Xencia Technology Solutions is seeking a Senior Data Engineer to design, build, and operate the data pipelines and lakehouse platform powering analytics across the business.

You will own end-to-end ingestion, transformation, and modeling on Databricks and Microsoft Fabric, turning raw data into reliable, analytics-ready datasets while mentoring peers and setting engineering standards.

Qualifications

• Proven track record in building and operating production data pipelines.
• Hands-on experience with Databricks, Spark, Delta Lake, and lakehouse architectures.
• Experience designing scalable batch and streaming data pipelines (ELT/ETL).
• Familiarity with Microsoft Fabric, its Lakehouse, Warehouses, and Dataflows.
• Proficient in Python and SQL; strong data modeling skills.
• Experience with Airflow and/or Azure Data Factory for orchestration.
• Knowledge of data governance tools like Unity Catalog & Purview.
• Exposure to Kafka/Event Hubs and Spark Structured Streaming.
• Experience with dbt, Terraform, Git, and CI/CD for data projects.

Responsibilities

• Build and operate scalable data pipelines (batch and streaming).
• Architect and implement a medallion lakehouse on Delta Lake; create analytics-ready models.
• Deliver data into Microsoft Fabric platforms and enable BI consumption.
• Orchestrate workflows with Airflow and/or Azure Data Factory; implement data quality checks and SLAs.
• Implement cataloging, lineage, and access controls using Unity Catalog and Purview.
• Tune Spark jobs and storage layouts for performance and cost efficiency.
• Define best practices, conduct design/code reviews, and mentor engineers.

Skills

Databricks

Spark

Python

SQL

Airflow

Azure Data Factory

Microsoft Fabric

Power BI

Delta Lake

Unity Catalog

Purview

Kafka

Event Hubs

dbt

Terraform

Git

CI/CD

ETL/ELT

Lakehouse

Pipelines

Tools

Databricks

Delta Lake

Unity Catalog

Purview

Apache Airflow

Azure Data Factory

Kafka

Event Hubs

dbt

Power BI

Terraform

Git

CI/CD

Job description

Senior Data Engineer

Location: 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

46 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 modern 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.