Databricks Lead

Ascendion Engineering; Bengaluru; Hybrid; INR 2,500,000 - 3,800,000; Full time

Job summary

Ascendion Engineering in Bengaluru is seeking a Data Engineer Lead to design, build, and optimize data pipelines and platforms supporting advanced analytics and BI across the organization. The role requires strong Databricks, SQL, AWS, and Airflow skills, and entails leading a team of data engineers, collaborating with cross-functional stakeholders, and delivering scalable, secure data solutions.

You will champion best practices in data governance, performance optimization, and cloud-native

Qualifications

• 6-8 years of experience in data engineering, with at least 3 years in Databricks.
• Deep hands-on expertise in: PySpark, Spark SQL, Delta Lake, Unity Catalog.
• Databricks Workflows, Delta Live Tables (DLT), SQL Warehouses, Photon.
• Strong proficiency in SQL for data modeling and query optimization.
• Solid understanding of AWS services (S3, Redshift, Glue, Lambda) for data engineering.

Responsibilities

• Build design specifications, data models, pipeline patterns, and solution architectures for the workstream.
• Lead the design, development, and maintenance of data pipelines and ETL workflows using Databricks and Airflow.
• Build reusable frameworks, templates, and engineering standards for ETL/ELT, streaming, and batch pipelines.
• Ensure cloud-native designs aligned with AWS platform best practices.
• Collaborate with stakeholders to understand data requirements and translate them into technical solutions and BI insights.

Skills

Databricks

PySpark

Spark SQL

Delta Lake

Unity Catalog

SQL

AWS

Airflow

Leadership

Data engineering

Tools

Databricks Workflows

Delta Live Tables

Photon

S3

Redshift

Glue

Lambda

Airflow

Job description

Role Overview

The Data Engineer Lead will be responsible for designing, building, and optimizing data pipelines and platforms to enable advanced analytics and business intelligence across the organization. This role requires strong expertise in Databricks, SQL, AWS, and Airflow, combined with a solid foundation in data analysis and engineering best practices. The ideal candidate will lead a team of data engineers, collaborate with cross-functional stakeholders, and ensure scalable, secure, and high-performing data solutions.

Key Responsibilities

Technical Design Design

• Build design specifications, data models, pipeline patterns, and solution architectures for the workstream.
• Lead the design, development, and maintenance of data pipelines and ETL workflows using Databricks and Airflow.
• Build reusable frameworks, templates, and engineering standards for ETL/ELT, streaming, and batch pipelines.
• Ensure cloud-native designs aligned with AWS platform best practices.

Governance, Security & Optimization

• Ensure data quality, integrity, and governance across data platforms.
• Optimize SQL queries and data models for performance and scalability.
• Build standards for Unity Catalog, lineage, metadata, glossary, and security policies.
• Build data quality frameworks, observability, and operational monitoring.

Cross-Functional Collaboration

• Work closely with stakeholders to understand data requirements and translate them into technical solutions.
• Collaborate with analytics and business teams to deliver actionable insights through BI dashboards and reports.
• Support estimations, and sizing for new programs and migrations.

AI/LLM Enablement (Advantage)

• Design frameworks for agentic workflows, GenAI-based automation, code generation, data quality validation, and metadata enrichment.
• Build Databricks Model Serving, Vector Search, and AI/BI integration.

Required Skills & Experience

• 6-8 8-18 years of experience in data engineering, with at least 3 years in Databricks.
• Deep hands-on expertise in: PySpark, Spark SQL, Delta Lake, Unity Catalog
• Databricks Workflows, Delta Live Tables (DLT), SQL Warehouses, Photon
• Streaming, batch, and real-time architectures
• Expertise in Databricks for big data processing and analytics.
• Strong proficiency in SQL for data modeling and query optimization.
• Solid understanding of AWS services (S3, Redshift, Glue, Lambda, etc) for data engineering.
• Strong analytical and problem-solving skills with attention to detail.
• Excellent communication and leadership skills to manage teams and stakeholders.

Preferred Qualifications

• Databricks Certified Data Engineer Professional or Databricks Architect certification.
• Experience with Databricks AI/BI, Lakehouse Federation, and Airflow.
• Familiarity with Airflow DAGs.
• AWS certification in data analytics or related specialization.
• Knowledge of LLMs, agentic frameworks, or GenAI automation (strong advantage).

Work Environment

This position is based in Bengaluru, Karnataka, India, and offers a hybrid work environment. Relocation is allowed for this role.