Lead Databricks Data Engineer

Namasys Analytics; India; On-site; INR 4,000,000 - 6,000,000; Full time

Benefits offered by this job

Certification support

Job summary

Namasys Analytics is seeking a Lead Databricks Data Engineer to own the data engineering workstream of a large-scale predictive analytics programme. You will architect and lead the build of production-grade data pipelines on Databricks, integrating SAP and Oracle into a governed lakehouse that feeds ML models, scoring engines, and dashboards.

You will lead a small engineering team, set standards for the programme and drive data quality, governance, and reliability across the pipeline lifecycle.

Qualifications

• 6+ years in data engineering with production Databricks delivery.
• Experience integrating SAP systems into cloud data platforms.
• Strong pipeline orchestration, data modelling and data quality engineering.
• Experience leading small engineering teams in fixed-deadline delivery.
• Clear technical communication with architects and stakeholders.

Responsibilities

• Architect end-to-end ingestion and transformation pipelines on Databricks from SAP and Oracle sources.
• Design integration approach for SAP data extraction within security and governance constraints.
• Implement data quality validation, anomaly detection, and lineage tracking.
• Lead and review the work of data engineers; ensure pipeline reliability through stages.
• Establish CI/CD deployment practices for data assets with client platform team.
• Contribute to solution architecture, estimation and technical documentation.

Skills

Databricks

Delta Lake

Spark

Workflows

Data modeling

Data quality engineering

CI/CD for data assets

Tools

SAP

Oracle

Job description

We are hiring a Lead Databricks Data Engineer to own the data engineering workstream of a large-scale predictive analytics programme. You will architect and lead the build of production-grade data pipelines on Databricks, integrating complex enterprise source systems (SAP and Oracle) into a governed lakehouse that feeds ML models, scoring engines, and executive dashboards. You will lead a small engineering team and set the standards the whole programme builds on.

What you'll do

• Architect end-to-end ingestion and transformation pipelines on Databricks (Delta Lake, Workflows, Unity Catalog) from SAP and Oracle source systems
• Design the integration approach for SAP data extraction (PM, MM, S/4HANA) in read-only patterns, working within enterprise security and data governance constraints
• Implement data quality validation, anomaly detection, and lineage tracking as first-class pipeline components with contractual quality thresholds
• Lead and review the work of data engineers; own pipeline reliability through SIT, UAT, go-live, and hypercare
• Establish CI/CD-based deployment practices for data assets in coordination with the client platform team
• Contribute to solution architecture, estimation, and technical documentation

What you'll need

• 6+ years in data engineering, with production Databricks delivery (Delta Lake, Spark, Workflows)
• Demonstrated experience integrating SAP systems (ideally PM/MM or S/4HANA) into cloud data platforms
• Strong pipeline orchestration, data modelling, and data quality engineering skills
• Experience leading small engineering teams in fixed-deadline delivery
• Clear technical communication with architects, security teams, and business stakeholders

Nice to have

• Databricks Certified Data Engineer Associate or Professional (certification support provided)
• Experience in asset-intensive or regulated industries
• Familiarity with Oracle P6 / EAM or finance data sources
• Prior delivery experience in the GCC region