Senior Data Engineer (India)
# Senior Data Engineer (India) **Alimentiv** · India · `Remote` · `Full Time` 💼 **Уровень роли:** `Senior` 💰 **Компенсация:** `2,094,639 – 3,603,725 INR` 🕒 **Статус:** *Опубликовано: сегодня* · *Источник: Himalayas (JSON API)* --- ### Top Skills & Match 🎯 **Ключевой стек роли:** `[Data-Engineer]` `[Lead-Data-Engineer]` `[Big-Data-Engineer]` `[Data-Architect]` `[Senior-Data-Engineering]` --- ### About the Role 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 . Data Architecture & Engineering - 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. . Data Integration & Automation - 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. . Analytics & Data Enablement - 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. Stakeholder Engagement & Leadership - 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 Job Experience & Education Requirements: Bachelor’s degree in Computer Science, Information Systems, Engineering, or related field (Master’s preferred) And 5–8 years of experience designing and developing enterprise-scale data solutions (data warehouses, data lakes, operational databases) Other: - 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. Originally posted on Himalayas
- Data-Engineer
- Lead-Data-Engineer
- Big-Data-Engineer
- Data-Architect
- Senior-Data-Engineering
Наблюдалась 2026-10-05, впервые 2026-10-05, источник — Himalayas (JSON API).