HYDERABAD · FULLTIME
IT&Data Engineer
Infosys
Hyderabad · onsite · Posted 12d ago
Sourced from
Undisclosed7–10 yrsfulltimeHyderabad
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Section · 01
About this role
Job Summary
Role purpose: He/she builds governed, reusable data products - contributing to OneHouse (the central lakehouse) and delivering transformations within Data Transformation Units (DTUs) - while raising the technical bar of the squad through mentoring, design guidance and code quality.
As a chapter member, the role provides technical leadership at squad level, but does not carry people-management, capacity or standard-setting accountabilities - which remain with the Chapter Manager and the Chapter Lead.
Level reporting note: This is an individual-contributor role at L9. The role reports to the DA Engineering Chapter Manager (L8), preserving the chapter reporting line (Chapter Lead Chapter Manager chapter team member). People-management, staffing and standard-setting are explicitly out of scope to keep the role distinct from the L8 Chapter Manager.
Main mission: Ensure, within a squad, the technical quality and reliability of data products delivered on OneSource 2.0 - acting as hands-on technical reference and coach - so that Bronze Silver Gold datasets serve as a trusted Single Source of Truth (SSOT), under the guidance of the Chapter Manager.
Roles Responsibilities - Act as the technical reference for the squad's data engineering work on OneSource 2.0
- Guide solution build within guardrails; drive design and code quality through peer review
- Mentor and upskill junior data engineers; support estimation and technical planning
- Contribute to Engineering Decision Records (EDRs) for implementation-level decisions
- Data ingestion (config-driven)
- Configure ingestion using the OneHouse metadata-driven framework: create/modify JSON configuration files (ingestion, Bronze) and deploy via GitHub / GitOps / CI-CD
- Onboard sources (SAP/DB2, files, Snowflake, external push/pull) into OneHouse, ensuring reliability, completeness and lineage
- Transformation data modelling (core value)
- Build Silver (cleaned, harmonized, modelled) and Gold (business aggregations / data products) datasets implementing business KPIs
- Apply and enrich reusable logic from the Transformations Library; document and version it
- Translate KPI definitions into scalable transformations aligned with domain data models
- Platform engineering within DTUs
- Develop within DTUs using Databricks (Spark/SQL/Delta Lake) and, where relevant, ADF, Snowflake or Informatica
- Structure data across Bronze / Silver / Gold; optimize performance, cost (FinOps) and scalability
- Apply best practices for CI/CD, IaC, monitoring and data quality checks
- Governance data products
- Verify integrity of ingested data and entities in Unity Catalog; respect GBDO / Data Owner validation and security-by-design
- Ensure only OneHouse-stored, catalogued data is published as shareable, certified data products (SSOT)
- Strong Data Engineer experience in enterprise environments, with hands-on OneSource 2.0 / OneHouse DTU practice
- Databricks (Spark/SQL, Delta Lake) mandatory; ADF / Azure stack; exposure to Snowflake / Informatica a plus
- Solid data modelling for analytics (facts, dimensions, derived metrics) and medallion architecture
- Comfortable with config-as-code / GitHub / CI-CD working model; experience integrating ERP / Finance / Commercial data (e.g. SAP)
- Leadership positioning (technical, not managerial)
- Recognized technical reference within the squad; able to coach juniors and justify design choices among competing alternatives
- Operates under the guidance of the Chapter Manager - no people-management, capacity or standard-setting accountability
- Building governed Bronze/Silver/Gold data products in OneHouse and DTUs, and coaching junior engineers - while reporting to the L8 Chapter Manager. Lead reflects technical seniority, not a management layer, keeping the role cleanly one level below the Chapter Manager in the chapter structure
- MCA,ME,MSc,MTech,Bachelor of Engineering,BE,BSc,BTech
- Technology->Data Engineering->Databricks
Data Analytics Unit
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Section · 02
Skills
data qualityInformaticaTerraformGithubDB2Data EngineerData ingestioncode qualityFinOpsGitOpsdata transformationlakehouseAnalyticsdata modelsJSONAzure StackDatabricksData EngineeringERPArchitectureMicrosoft Azurefinance
Section · Company
About Infosys
Infosys
IT Services & Consulting
323.6k+
employees
1981
45 years old
Bengaluru/Bangalore, Karnataka
India
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