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Data Platform Software Engineer — Lead

CloudIngest

5 - 10 years

Bengaluru

Posted: 15/05/2026

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Job Description

Job Title: Data Platform Software Engineer Lead

Location: Bangalore, Karnataka India

Minimum Experience: 8-13 month contract with multiple extensions


ROLE OVERVIEW

We are looking for a Data Platform Lead to own the design, build, and governance of our enterprise data platform. This is a role within the Data COE, responsible for driving platform maturity across a federated, multi-cloud environment. You will set engineering standards, eliminate data duplication and drift across domains, and enable reliable, governed data access without creating centralisation bottlenecks.


KEY RESPONSIBILITIES

  • Design and evolve the enterprise data platform spanning Snowflake and Databricks across Azure and AWS
  • Build and maintain production-grade ELT/ETL pipelines using Spark, dbt, Airflow, and Kafka
  • Define and enforce platform standards for ingestion, transformation, storage, and access across federated domain teams
  • Drive data quality, data contract adoption, and lineage visibility across the estate
  • Own cloud storage architecture across S3 and ADLS; lead CI/CD practices for all platform assets
  • Lead containerized workload deployment using Kubernetes for data platform services
  • Coordinate with domain teams to align on standards; represent platform engineering in architecture forums
  • Mentor mid-level engineers and conduct technical design reviews for platform-impacting changes


MUST-HAVE SKILLS

  • Snowflake expert-level: data modelling, performance tuning, role-based access, zero-copy sharing, dynamic data masking
  • Databricks production experience: Delta Lake, Unity Catalog, cluster management, Databricks Workflows
  • Python and SQL strong proficiency; Scala advantageous
  • Apache Spark distributed data processing at scale
  • Apache Kafka real-time event streaming, pipeline design, topic management
  • Apache Airflow pipeline orchestration, DAG design, dependency management
  • dbt transformation layer modelling, testing, documentation
  • Cloud storage S3 and ADLS; familiarity with Parquet, Delta, and partitioning strategies
  • Kubernetes container orchestration for data platform services
  • CI/CD GitHub Actions or equivalent for data platform assets (pipelines, schemas, infra)
  • 8+ years of data engineering experience, with 3+ years in a lead or staff IC capacity


GOOD-TO-HAVE SKILLS

  • Data quality frameworks Great Expectations or equivalent, embedded in pipeline execution
  • Feature Store platforms Feast, Tecton, or equivalent; ML data infrastructure design
  • Data catalogue and lineage tooling Amundsen, DataHub, or equivalent
  • Data contracts as an engineering practice schema registries, versioning, producer/consumer agreements
  • Open table formats Apache Iceberg; lakehouse architecture patterns
  • Cross-cloud experience Snowflake (Azure), Databricks, and BigQuery integrations


WHAT WE'RE LOOKING FOR

  • Systems thinker able to see how pipeline, storage, and governance decisions interact at scale
  • Able to influence without authority across autonomous, federated domain teams
  • Opinionated on standards and quality, but pragmatic in how they are adopted across an existing estate
  • Strong communicator able to translate platform complexity to both engineering peers and business stakeholders
  • Ownership-driven, with a track record of improving platform reliability, cost efficiency, and developer experience

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