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Open nowPosted 11 hours ago

Senior Data Engineer (India)

alimentiv-235 open roles

Where
Bangalore
Work mode
Remote
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Your applicationOpen nowSenior Data Engineer (India)alimentiv-2 · Bangalore

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The clock on this job

Early applications get read.

7.8% of postings close within 7 days. Measured by our own scanner across the market. alimentiv-2 postings stay open a median of 4 days.

Share of postings closed within
  1. 1.7%1 day
  2. 3.5%3 days
  3. 7.8%7 days
  4. 14.6%14 days
  5. 34.1%30 days
This job: posted 11 hours ago

alimentiv-2 median: 4 days open

The posting

The Lead Data Engineer will design, build, and operationalize scalable data solutions to support enterprise analytics and AI/ML initiatives. This role requires expert-level proficiency in Databricks, Azure Fabric, PySpark, SQL, and the Azure ecosystem, with deep experience across data warehouses, data lakes, and real-time integration. The Lead Data Engineer will architect end-to-end pipelines using industry-standard tools, drive automation, and move solutions effectively into production. The incumbent will ensure compliance with data governance requirements (including GxP and HIPAA/GDPR) while building reusable, integrated pipelines and analytical models that promote self-service analytics. This role provides technical leadership across the team, mentors junior engineers, and partners with business stakeholders to align data engineering with organizational objectives.

About the Role

  • Architect, design, and implement end-to-end data solutions using Azure Databricks, PySpark, Azure Data Factory, and Azure SQL.
  • Design, build, and maintain data pipelines from data sources through integration to consumption for specific use cases.
  • Implement robust data modeling standards across bronze, silver, and gold layers in the data lake.
  • Develop data models (conceptual, logical, and/or physical) as required.
  • Optimize Spark and SQL workloads for performance, scalability, and cost efficiency.
  • Manage metadata using data preparation, integration, and AI-enabled tools and techniques.
  • Drive automation in data integration; recommend and lead implementation of techniques to automate repeatable data preparation and integration tasks.
  • Build API-based integrations (REST/JSON) and real-time ingestion frameworks.
  • Automate data workflows using Azure DevOps pipelines and Git-based CI/CD practices.
  • Implement parameterized, reusable pipeline templates for ingestion and transformation.
  • Develop automated unit, regression, and integration testing frameworks for data jobs.
  • Prepare and curate high-quality datasets for BI, reporting, and advanced analytics.
  • Partner with analytics teams using Power BI, Tableau, or similar platforms to define semantic models and KPIs.
  • Implement performance-optimized data models for self-service analytics.
  • Will occasionally provide support to end users on the use of data visualization solutions.
  • Lead technical design reviews, mentor junior engineers, and promote best practices.
  • Assist cross-functional groups, business analysts, and stakeholders to gather, define, and refine data requirements.
  • Collaborate with business and IT stakeholders to align data engineering with organizational objectives.
  • Propose innovative data ingestion, preparation, and integration techniques to address stakeholder requirements.
  • Contribute to architectural roadmaps and technology evaluations for the data platform.
  • In collaboration with functional leaders, identify inefficiencies and recommend improvements to the executive team.

About You

  • Expert-level proficiency in Databricks, Azure Fabric, PySpark, SQL, and Azure DevOps.
  • Proven experience with Azure Data Factory, ADLS Gen2, and Azure SQL Server.
  • Strong experience with Microsoft Azure data management architectures including Data Warehouse, Data Lake, and Data Catalogue, and supporting processes such as Data Integration, Governance, and Metadata Management.
  • Experience with Power BI required; Tableau or Looker a plus.
  • Working knowledge of CI/CD automation, version control (Git), and infrastructure as code (ARM, Bicep, or Terraform).
  • Experience in life sciences or healthcare industries is a strong plus.
  • Good understanding of GxP, GDPR/HIPAA, and applicable CFR/CTR/CTD regulations.
  • Demonstrated success working with both IT and business stakeholders while integrating analytics and data science output into business processes and workflows.
  • Must have excellent written and verbal communication skills.
  • Proven ability to work independently and as part of a team and meet important deadlines.
  • Statistical analysis skills are an asset.
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