Job Description : Senior Data Engineer / Data Engineering Lead

Experience : 10+ Years

Location : Chandigarh

Work Model : Work from office

Domain : Banking / Financial Services / Credit Risk

Role Type : Full-Time

About the Role :

We are seeking an experienced Data Engineer with 10+ years of expertise in building and modernizing data assets for banking portfolio optimization. The role offers an opportunity to lead teams in modernizing BI, AI, and ML data pipelines, automate manual processes, and build audit-ready production data platforms. The successful candidate will work on impactful projects across wholesale lending, retail lending, and credit risk, collaborating with global stakeholders and driving data transformation initiatives.

Key Responsibilities :

- Lead the architecture and development of end-to-end analytics platforms.

- Develop and maintain BI, analytics, and reporting data pipelines.

- Set up AWS Glue for file ingestion and data bucket management.

- Partner with client teams to deploy Databricks workspaces with secure governance.

- Refactor existing SAS scripts into Spark jobs using Databricks Notebooks.

- Build PySpark / Spark SQL ELT jobs using Delta Tables for ACID compliance.

- Orchestrate PySpark transformations using Databricks Workflows.

- Develop and manage monthly batch-processing analytics data pipelines.

- Lead BI development teams supporting credit risk and lending transformation projects.

- Analyze data lineage and implement data accuracy and validation testing.

- Design and develop dashboards based on stakeholder requirements.

- Test and deploy dashboards with row-level data security.

- Transition decision-making analytics dashboards into production.

- Collaborate with global stakeholders to understand business requirements and deliver scalable data solutions.

- Drive modernization, automation, data quality, and production-readiness initiatives.

Required Skills & Qualifications :

Must Have :

- 10+ years of experience in Data Engineering / Data Analytics / BI.

- Strong experience with Python programming.

- Hands-on expertise in PySpark.

- Advanced SQL skills.

- Strong hands-on experience with Databricks.

- Experience with AWS Glue.

- Strong experience with Tableau.

- AWS Certified Data Engineer - Associate certification.

- Experience working with large-scale data pipelines and analytics platforms.

- Strong understanding of data engineering practices and production data environments.

Good to Have :

- SAS programming experience.

- Strong knowledge of Spark SQL.

- Experience with data pipeline development and orchestration.

- Knowledge of data governance, lineage, and data quality frameworks.

- Experience in banking, lending, credit risk, or financial services.

- Experience leading data engineering or BI development teams.

Bonus :

- Advanced prompt engineering experience.

- Exposure to AI/ML data pipelines and AI-driven analytics.

Domain Experience :

Experience in any of the following areas will be highly valuable :

- Wholesale Lending

- Retail Lending

- Credit Risk

- Banking Portfolio Optimization

- Financial Services Analytics

- BI & Decision-Making Analytics

What We Offer :

- Opportunity to work on high-impact banking and financial services transformation projects.

- Exposure to modern AWS, Databricks, Spark, AI/ML, and BI technologies.

- Opportunity to lead data engineering and BI transformation initiatives.

- Collaboration with global stakeholders and client teams.

- Health Insurance.

- Paid Time Off.

- Learning & Development Opportunities.