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Role Description
ROLE SUMMARY
The Senior Data Engineer (India) is the in-region counterpart to US-based Senior Data Engineers on the HR Analytics India delivery team. This role partners with US Sr Data Engineers who lead direct business decomposition with HR stakeholders, then carries that context into the India working day to lead delivery across the same end-to-end vertical — from ingestion, through modeling and transformation, into the Microsoft Fabric semantic layer and Power BI visualizations. Because overlap hours with US business stakeholders are limited, this role must understand the HR business deeply enough to anticipate intent, resolve ambiguity without round-tripping every question, and make sound delivery decisions during India hours. The Senior Data Engineer (India) should be able to act in a lead capacity for the India engineering pod, partners with US Sr Data Engineers and HR business teams, and is accountable for the quality, velocity, and reliability of what the India team ships.
WHY THIS ROLE EXISTS
The HR Analytics engineering team operates across the US and India. US-based Senior Data Engineers own primary business engagement and solution decomposition. The India team carries delivery momentum through hours when US stakeholders are offline, which means the India Senior Data Engineer cannot rely on synchronous clarification for every decision. Strong business understanding is not a nice-to-have for this role — it is the single most important attribute, because it is the mechanism that lets India delivery move forward at full speed across the timezone gap.
How This Role Operates Across The Timezone Gap
- Uses the daily overlap window with US counterparts intentionally — for decomposition handoffs, design review, risk escalation, and decisions that genuinely require synchronous discussion — not for clarifying questions that strong business context would have already answered.
- Carries the business intent behind each deliverable into the India working day, so the India team can make sound decisions on edge cases, transformation logic, and design tradeoffs without waiting for US hours.
- Maintains async-first communication discipline: well-documented designs, clear decision logs, and written status that lets US counterparts pick up context cleanly each morning.
- Proactively flags risks, blockers, and decisions needed in time for US counterparts to act on them before the next overlap window closes.
- Joins HR business stakeholder meetings during overlap hours when possible, to build firsthand business context that informs decisions during India-only hours.
How The Team Works Together
- The HR Analytics engineering team operates as a single team across the US and India, with clear layers and a shared way of working:
- The HR Analytics engineering team is structured in three layers that work together: an Information Architect who owns end-to-end architecture and engineering standards; Principal Data Engineers who set the engineering bar and lead the data engineering team; and Senior Data Engineers, Data Engineers, and Associate Data Engineers who deliver data products across the full vertical.
- The team operates across the US (Frisco, TX) and India (Hyderabad) and US locations in PST Timezone, with engineers in all regions partnering across the timezone gap to keep delivery moving and to share ownership of data products end-to-end.
- Business engagement happens through the team's senior engineering and architecture leadership, with broader engineering team participation that grows over time as engineers build domain context and earn trust with stakeholders.
- Work flows from a business need into a technical solution design, then into a build that spans ingestion through the unified framework, data modeling, transformation across Snowflake and Databricks, semantic layer in Microsoft Fabric, and visualization in Power BI — with quality, testing, documentation, and reliability owned across the whole vertical.
- The team operates a DevOps model — engineers own their data products in production, share an on-call schedule, and rotate the operations role across the team.
- This role is a senior delivery engineer in India who partners with US-based senior engineers, carries business context into India hours, and leads delivery across the timezone gap.
Core Responsibilities
- Serve as the senior technical lead for the HR Analytics India delivery pod, owning the quality, velocity, and reliability of what the India team ships across the full vertical from ingestion through visualization.
- Partner with US-based Senior Data Engineers as the in-region counterpart — taking handoff of decomposed solution designs, asking the right clarifying questions during overlap windows, and carrying the work forward independently during India hours.
- Understand the HR business deeply enough to interpret intent behind requirements, resolve ambiguity in the moment, and make sound delivery decisions when US stakeholders are unavailable.
- Lead and mentor the India engineering team — coaching mid-level and junior engineers, reviewing their code and designs, raising the technical and business-context ceiling of the pod.
- Contribute hands-on to complex pipeline builds, semantic models, and high-risk implementations rather than only directing the work of others.
- Implement end-to-end data products in the team's stack: ingestion through the unified framework, data modeling, transformation in Snowflake (including Iceberg tables) and Databricks (Delta Lake, Unity Catalog), semantic layer build in Microsoft Fabric (Fabric IQ, OneLake), and Power BI visualization.
- Lead design reviews in India hours, ensuring solutions align with the patterns set by the team's Information Architect and the designs handed off from US Sr Data Engineers.
- Own pipeline KTLO (Keep the Lights On) coverage during India hours, including monitoring, incident response, and providing engineering continuity across the timezone gap.
- Maintain rigorous documentation — source-to-target mappings, data lineage, decision logs, runbooks, and status artifacts that enable async collaboration with US counterparts.
- Implement and uphold testing discipline — unit tests, integration tests, data quality checks, reconciliation logic, and SLA-driven ing.
- Contribute to and uphold the team's DevOps practices — Git, CI/CD, automated testing, and code review — including being a senior reviewer for India-team pull requests.
- Participate in HR business stakeholder meetings during overlap windows when possible, building direct business context and the trust that lets the India team move faster.
- Grow over time toward greater direct business engagement, as overlap and trust allow.
Required Qualifications
- Bachelor's degree in Computer Science, Software Engineering, Information Management, or equivalent experience in field — plus 8+ years of related work experience.
- Must be located in India.
- 8+ years of hands-on data engineering experience delivering production data pipelines and data products in large enterprise environments.
- Proven track record of leading data engineering delivery from an India location while partnering with US-based business and engineering counterparts across a significant timezone gap.
- Demonstrated business acumen — the ability to understand a functional domain (HR, finance, supply chain, or comparable) deeply enough to interpret intent, resolve ambiguity, and make sound delivery decisions without synchronous access to business stakeholders.
- Experience mentoring and technically leading offshore or in-region engineering pods, including raising both technical quality and business-context understanding of the team.
- Expert proficiency in SQL and Python, including PySpark and Spark SQL for distributed data transformation.
- Hands-on experience with Databricks including Delta Lake, Unity Catalog, and workflow orchestration.
- Hands-on experience with Snowflake at production scale, including experience with Iceberg tables and modern open table formats.
- Hands-on experience with Microsoft Fabric including OneLake and Fabric IQ semantic layer design, with a track record of publishing certified data products for downstream consumption.
- Hands-on experience building data visualizations and reports in Power BI, including semantic model design that bridges Fabric models to BI consumption.
- Experience landing data through a unified ingestion framework and implementing data contracts with source systems.
- Strong data modeling skills — conceptual, logical, and physical — including dimensional modeling and modern lakehouse modeling patterns.
- Experience implementing data quality frameworks and pipeline testing, including unit tests, integration tests, data quality checks, and reconciliation.
- Experience with DevOps practices for data pipelines — Git, CI/CD, and automated testing.
- Excellent written and verbal English communication skills — including the async writing discipline that distributed delivery requires (clear designs, decision logs, status updates, written escalation).
- Strong problem-solving skills and the ability to operate independently on complex technical problems in ambiguous, high-pressure environments.
- Willingness and ability to flex working hours into the US overlap window as needed.
Preferred Qualifications
- Experience with HR data domains — talent acquisition, workforce analytics, compensation, learning, performance, or people analytics.
- Hands-on experience with Workday, ServiceNow HR, or comparable HR systems of record as authoritative sources for analytics.
- Experience working within a Global Capability Center (GCC) or offshore engineering model partnering with a US-based business and engineering function.
- Experience with real-time streaming technologies including Kafka, Azure Event Hub, Delta Live Tables, or Spark Structured Streaming.
- Experience with AI/ML pipelines, feature stores, or building data products that support generative AI and ML workloads.
- Familiarity with legacy data platforms such as Teradata, Oracle, or SQL Server in interoperating or migration contexts.
- Azure certifications or demonstrated experience with Azure-native data platform services beyond Fabric and Databricks.
- Familiarity with T-Mobile's Omni lakehouse platform, MagentaBuilt integrations, or enterprise IT architecture standards.
- Experience with data privacy and regulatory compliance for HR data (GDPR, CCPA, employee data protection).
Skills
data engineering,power bi,python,sql,
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