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Lead Data Engineer

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Onsite

Lead Data Engineer

UST

Lead Data Engineer

Skills

SQL QueriesData EngineeringPythonSnowflakeGitData AnalysisdbtPySpark

1 month ago

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Important information


Contract type:

Permanent

Location:

Bengaluru, Karnataka, India

Work mode:

Onsite

Published on:

7 September 2026

What they need


Role Description Job Code 15124 Locations Bengaluru Minimum Experience 6 Maximum Experience 8 Mandatory Skills Snowflake,SQL,Python,PySpark,dbt,ETL/ELT,data modeling,Git Skill to Evaluate Snowflake,SQL,Python,PySpark,dbt,ETL/ELT,data modeling,Git Experience 6 to 8 Years Location Bengaluru Job Description Required qualifications

  • Bachelor's or master's degree in computer science, engineering, mathematics or a related discipline, or equivalent practical experience.
  • Substantial professional experience designing and operating enterprise data pipelines and data warehouses in production.
  • Advanced SQL skills and strong hands-on experience with Python and/or PySpark for data processing and automation.
  • Deep experience with Snowflake, including performance optimization, security, workload management and scalable data modeling.
  • Experience building ETL/ELT solutions with dbt, Informatica PowerCenter or comparable transformation and integration tools.
  • Hands-on experience implementing CI/CD pipelines for data engineering workloads using Git-based workflows and automated testing/deployment tools.
  • Experience building automated data quality systems with measurable rules, ing, lineage and issue-resolution workflows.
  • Strong grounding in data profiling, cleansing, standardization, reconciliation and production data validation.
  • Ability to gather ambiguous requirements, make sound design decisions and communicate effectively with technical and non-technical partners. Preferred qualifications
  • Snowflake SnowPro Core or comparable cloud data certification.
  • Experience with REST API, event and/or streaming data, and high-volume security or operational datasets.
  • Familiarity with data observability and quality frameworks such as dbt tests, Great Expectations, Soda or Deequ.
  • Experience delivering data solutions in regulated, security-sensitive, healthcare, telecommunications or audit-oriented environments.
  • Demonstrated technical leadership, mentoring or delivery coordination across a small engineering team. Education Qualificaiton B Tech/ M Tech Job Title Senior Data Engineer (Senior Individual Contributor / Technical Lead) Roles & Responsibilities
  • Design and deliver scalable pipelines. Build batch and near-real-time ETL/ELT pipelines using SQL, Python and PySpark, with Snowflake as a primary cloud data platform.
  • Engineer reliable data models. Create dimensional, normalized and analytical models that support efficient querying, traceability and reuse across enterprise reporting and analytics.
  • Own data quality by design. Implement automated profiling, schema checks, reconciliation, completeness, freshness, uniqueness and business-rule validation; publish quality results and route failures for action.
  • Build CI/CD for data products. Create and maintain automated build, test and deployment pipelines for SQL, dbt, orchestration code and infrastructure configuration, including version control, peer review, environment promotion and safe rollback.
  • Strengthen observability and operations. Monitor pipeline health, lineage, cost, performance and service-level objectives; troubleshoot incidents, perform root-cause analysis and eliminate recurring manual support.
  • Integrate diverse sources. Ingest and standardize data from databases, APIs, files and event sources, applying secure access patterns and appropriate handling for sensitive information.
  • Modernize legacy workflows. Migrate or refactor Informatica PowerCenter and other legacy ETL processes into maintainable cloud-native patterns using tools such as dbt and modern orchestration platforms.
  • Partner from requirement to adoption. Translate stakeholder needs into technical designs, validate production outcomes and communicate tradeoffs, risks and delivery progress clearly.
  • Lead through engineering practice. Set coding and testing standards, review designs and pull requests, mentor engineers and coordinate delivery across cross-functional teams.

Skills SQL, Python, Snowflake, PySpark

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