Overview:

Role Overview: The Lead Engineer holds day-to-day engineering leadership of the pod on this engagement. This role works daily with the onshore technical lead to review open questions, resolve ambiguity, and ensure the pod team has clear, prioritized work at all times — at the start of each sprint and throughout it.

The Lead Engineer serves as the primary technical liaison between the onshore Core Team and the hybrid internal team, translating backlog items into assignable tasks, tracking progress against sprint goals daily, and escalating blockers promptly.

This role carries technical and delivery accountability beyond task coordination. The Lead Engineer is expected to ask the clarifying questions that prevent rework, challenge ambiguity rather than work around it, and maintain a consistent pace of delivery across the pod.

Responsibilities:

Roles & Responsibilities:

- Meet daily with the onshore technical lead to review open questions, clarify requirements, and confirm priorities.
- Translate sprint-level backlog items into clear, appropriately scoped tasks, ensuring assignments are made at the start of each sprint.
- Lead daily check-ins with the pod to track progress against sprint goals, resolve blockers, and adjust task sequencing as priorities change.
- Design and build complex Databricks pipelines (Bronze through Gold) for financial and operational data, setting the technical standard for the pod.
- Own technical quality for the pod's output, including code review, data quality validation, and adherence to the platform's security model (RLS/CLS).
- Identify risks, dependencies, and scope gaps early, and escalate them to the onshore lead outside of standing meetings when necessary.




- Lead the pod's knowledge transfer from the onshore Integration & Middleware team on Boomi integration patterns (e.g., JDE-Concur, JDE-UKG), and plan the pod's transition to build, validation, and support responsibility for those integrations.
- Mentor Senior and Data Engineers on the pod, developing their ability to work independently and resolve ambiguity on their own.
- Communicate the pod's capacity and constraints accurately, including flagging when scope exceeds available bandwidth.

Qualifications:

Required Qualifications

- 8+ years of data engineering experience, including substantial hands-on work with Databricks (Spark/PySpark, Delta Lake, Unity Catalog, Databricks Workflows).
- Databricks Certified Data Engineer Professional required (Associate accepted if Professional certification is in progress).
- Strong SQL and Python skills, with the ability to review and provide feedback on others' code.
- Demonstrated experience building data pipelines from financial or ERP source systems — JD Edwards (JDE) directly preferred, with Eco Sys or Microsoft Dynamics also relevant — into a governed lakehouse or warehouse, including general ledger, cost, and project financial data.
- Experience connecting operational and financial data to core business reporting within a construction, EPC, energy, or other asset-heavy industry (e.g., cost-to-complete, earned value management, project P&L;).




- Prior experience in a hybrid onshore/offshore delivery model (dedicated onshore lead plus offshore engineering pod), ideally in the offshore lead role.
- Demonstrated experience leading or co-leading agile delivery teams, including sprint planning, backlog grooming, and daily standups.
- Strong written and verbal English communication skills, including the ability to lead meetings and discussions directly with onshore and client stakeholders.
- Working knowledge of iPaaS/integration middleware platforms, with Boomi strongly preferred; candidates without direct Boomi experience should demonstrate the ability to ramp quickly through structured knowledge transfer.

Preferred Qualifications

- Experience implementing row-level or column-level security (RLS/CLS) in Databricks Unity Catalog.
- Familiarity with Databricks Genie (AI/BI) or comparable self-service analytics tooling.
- Experience with CI/CD for data pipelines (Databricks Asset Bundles, Git Hub Actions, Azure Dev Ops, or similar).
- Familiarity with Power BI or other BI tools consuming governed Gold-layer data.
- Experience with API-based integration (REST/webhook patterns) and file-based integration (EDI, flat file, CSV) with validation controls.

Qualified Attributes:

- Operates effectively in ambiguity; asks precise clarifying questions rather than making assumptions.
- Prioritizes early clarity to maintain delivery speed, and acts decisively once requirements are understood.
- Takes ownership of outcomes rather than assigned tasks alone, and raises concerns when something does not align.
- Communicates directly and proactively across time zones and cultures without requiring prompting.
- Has prior experience in a onshore/offshore hybrid delivery model and understands the trust, transparency, and delivery discipline it requires.

📌 Lead Engineer- Databricks & Data Engg (Hyderabad)
🏢 Nameless
📍 Hyderabad