Data Engineering Lead

Ness Digital Engineering

Data Engineering Lead managing enterprise-scale data platforms using AWS, Snowflake, and Databricks in financial services. Leading data engineering teams and ensuring data governance.

Posted 5/4/2026full-timeBangalore • 🇮🇳 IndiaSeniorWebsite

Tech Stack

Tools & technologies

Amazon RedshiftAWSETLPySparkSparkSQL

About the role

Key responsibilities & impact

Lead the design and implementation of enterprise data platforms (Data Lakes, Lakehouse, DWH)
Architect scalable, secure, and high-performance data architectures on AWS
Build modern ETL/ELT pipelines using PySpark, SQL, Spark
Implement AWS services (S3, Glue, EMR, Lambda, Redshift)
Lead and mentor data engineering teams
Define best practices, reusable frameworks, and coding standards
Enable enterprise analytics through curated data models
Ensure data governance, quality, and lineage
Optimize pipelines for performance and cost
Work closely with financial domain stakeholders

Requirements

What you’ll need

10–15 years of experience in Data Engineering / Analytics
Strong AWS, Snowflake, Databricks experience
Experience building enterprise data lakes and lakehouses
Experience in Financial Services / Banking / Capital Markets
AWS Certified Solutions Architect / Data Analytics (Preferred)
Databricks Certified Data Engineer (Preferred)
Snowflake SnowPro Certification (Preferred)

Benefits

Comp & perks

Health insurance
Professional development
Flexible work arrangements
Paid time off

ATS Keywords

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Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

data engineeringETLELTPySparkSQLSparkdata governancedata qualitydata lineagedata architecture

Soft Skills

leadershipmentoringcollaborationcommunicationbest practices definition

Certifications

AWS Certified Solutions ArchitectAWS Certified Data AnalyticsDatabricks Certified Data EngineerSnowflake SnowPro Certification