Sr Data Engineer(Python)

Summit Consulting Services; Bengaluru Urban; On-site; INR 3,500,000 - 5,500,000; Full time

Job summary

Summit Consulting Services Bengaluru seeks a senior data engineer to design, build, and optimize large-scale data pipelines on Databricks Lakehouse, ensuring reliability, scalability, and governance across the enterprise.

You will modernize Azure-based data ecosystems, implement Delta Lake models, Unity Catalog, and automate CI/CD workflows, collaborating with cross-functional teams on data modeling, security, and downstream consumption for analytics and applications.

Qualifications

• 10+ years of experience designing and developing scalable data pipelines in modern data warehousing environments.
• Expertise in data engineering and data warehousing, delivering enterprise-grade solutions.
• Proven ability to lead and coordinate data initiatives across cross-functional organizations.
• Advanced proficiency in SQL, Python, and ETL/ELT frameworks with performance tuning.
• Hands-on experience with Azure, Snowflake, and Databricks, and integration with enterprise systems.

Responsibilities

• Design and build scalable data pipelines end-to-end with governance.
• Implement and optimize Delta Lake data models for reliability and performance.
• Configure Unity Catalog for RBAC, lineage, and secure data sharing.
• Automate deployments, CI/CD workflows, and testing pipelines.
• Collaborate across Azure, Databricks, and enterprise systems to enable analytics.

Skills

SQL

Python

ETL/ELT

Data Modeling

Governance

Data Warehousing

Leadership

Tools

Databricks

Azure

Airflow

Delta Lake

Unity Catalog

REST APIs

CI/CD

Snowflake

Job description

Design, build, and optimize large-scale data pipelines on the Databricks Lakehouse platform, ensuring reliability, scalability, and governance.

Modernize the Azure-based data ecosystem, contributing to cloud architecture, distributed data engineering, data modeling, security, and CI/CD automation.

Utilize Apache Airflow and similar tools for orchestration and workflow automation.

Work with financial or regulated datasets, applying strong compliance and governance practices.

Develop and optimize ETL/ELT pipelines using Python, PySpark, Spark SQL, and Databricks notebooks.

Design and optimize Delta Lake data models for reliability, performance, and scalability.

Implement and manage Unity Catalog for RBAC, lineage, governance, and secure data sharing.

Build reusable frameworks using Databricks Workflows, Repos, and Delta Live Tables.

Create scalable ingestion pipelines for APIs, databases, files, streaming sources, and MDM systems.

Automate API ingestion and workflows using Python and REST APIs.

Support data governance, lineage, cataloging, and metadata initiatives.

Enable downstream consumption for BI, data science, and application workloads.

Write optimized SQL/T-SQL queries, stored procedures, and curated datasets for reporting.

Automate deployments, DevOps workflows, testing pipelines, and workspace configuration.

Technical Skills:

10+ years of experience designing and developing scalable data pipelines in modern data warehousing environments, with full ownership of end-to-end delivery.

Expertise in data engineering and data warehousing, consistently delivering enterprise-grade solutions.

Proven ability to lead and coordinate data initiatives across cross-functional and matrixed organizations.

Advanced proficiency in SQL, Python, and ETL/ELT frameworks, including performance tuning and optimization.

Hands-on experience with Azure, Snowflake, and Databricks, and integration with enterprise systems.