Lead Data Engineer (Must have exp. in Fivetran)

Posted on July 1, 2025

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Job Description

  • Lead Data Engineer (Must have exp. in Fivetran)
  • Strong hands-on expertise in SQL, DBT and Python for data processing and transformation.
  • Lead the design and development of data pipelines (batch and real-time) using modern cloud-native technologies (Azure, Snowflake, DBT, Python).
  • minimum 8 to 10 years
  • Expertise in Azure data services (e.g., Azure Data Factory, Synapse, Event Hub) and orchestration tools.
  • Translate business and data requirements into scalable data integration designs.
  • Strong experience with Snowflake � including schema design, performance tuning, and security model.
  • Guide and review development work across data engineering team members (onshore and offshore).
  • Good understanding of DBT for transformation layer and modular pipeline design.
  • Define and enforce best practices for coding, testing, version control, CI/CD, data quality, and pipeline monitoring.
  • Hands-on with Git and version control practices � branching, pull requests, code reviews.
  • Collaborate with data analysts, architects, and business stakeholders to ensure data solutions are aligned with business goals.
  • Understanding of DevOps/DataOps principles � CI/CD for data pipelines, testing, monitoring.
  • Own and drive end-to-end data engineering workstreams � from design to production deployment and support.
  • Knowledge of data modeling techniques � Star schema, Data Vault, Normalization/Denormalization.
  • Provide architectural and technical guidance on platform setup, performance tuning, cost optimization, and data security.
  • Experience with real-time data processing architectures is a strong plus.
  • Drive data engineering standards and reusable patterns across projects to ensure scalability, maintainability, and reusability of code and data assets.
  • Proven leadership experience � should be able to mentor team members, take ownership, make design decisions independently.
  • Define and oversee data quality frameworks to proactively detect, report, and resolve data issues across ingestion, transformation, and consumption layers.
  • Strong sense of ownership, accountability, and solution-oriented mindset.
  • Act as a technical go-to team member for complex design, performance, or integration issues across multiple teams and tools (e.g., DBT + Snowflake + Azure pipelines).
  • Ability to handle ambiguity and work independently with minimal supervision.
  • Contribute to hand on development as well for the ned to end integration pipelines and workflows.
  • Clear and confident communication (written and verbal) � must be able to represent design and architecture decisions.
  • Document using Excel, Word, or tools like Confluence.

Required Skills

(e.g. azure data factory synapse event hub)