Data Engineer

The DW Data Engineer will play a critical role in building, enhancing, and optimizing FMCG enterprise analytics platform. This individual will design and develop ETL/ELT pipelines, Lakehouse/Warehouse models, and curated datasets that power reporting and analytics across all business units of FMCG enterprise. This position works closely with BI Analysts, BI Developers, Architects, and business stakeholders to ensure that high-quality, scalable, and governed data is made available for decision-making

Role and Responsibilities

1.Data Engineering & Pipeline Development

• Design, build, and maintain ETL/ELT pipelines using Microsoft Fabric (Pipelines, Dataflows Gen2, Notebooks, Spark) and legacy SSIS.
• Develop ingestion frameworks for flat files (CSV/Excel), APIs, SaaS platforms, cloud feeds, and partner data.
• Implement medallion architecture (Bronze, Silver, Gold) using Lakehouse (Delta Lake), Warehouse, and OneLake.
• Automate data transformations using SQL, PySpark, and Fabric Notebooks.

2.Data Modeling & Optimization

• Build and optimize star schema models, conformed dimensions, and fact tables for BI consumption.
• Implement incremental loads, SCD handling (Type 1/2), partitioning, Z-ordering, compaction, and other Delta Lake optimization techniques.
• Collaborate with BI Analysts to translate business requirements into performant data models.

3.Data Quality, Governance & Security

• Ensure end-to-end data quality through validation, reconciliations, profiling, and automated tests.
• Apply governance principles using Purview for lineage, classification, and data cataloging.
• Enforce Row-Level Security (RLS), object-level security, and access controls across Fabric datasets.

4.Cross-Team Collaboration

• Partner with BI Analysts and Business Stakeholders to understand KPIs, metrics, and reporting requirements.
• Work with Architects to establish data platform standards, naming conventions, folder structures, and version control patterns.
• Provide technical expertise during UAT, troubleshooting, and performance tuning.

5.Operational Excellence

Monitor pipeline performance and proactively resolve pipeline failures.

Implement CI/CD practices using Azure DevOps / Git integration for code and artifact promotion across Dev, Stage, and Prod.

Contribute to documentation of data flows, data dictionaries, technical specifications, and workflows.

Qualifications and Education Requirements

• Bachelor’s degree in Computer Science, Information Systems, Engineering, or related field.
• 5+ years of experience in data engineering, BI development, or data warehouse development.
• Strong SQL skills (T-SQL) for complex transforms, joins, window functions, and performance tuning.
• Hands-on experience with Microsoft Fabric (Lakehouse, Warehouse, OneLake, Pipelines, Dataflows Gen2, Notebooks).
• Experience with Delta Lake, parquet, and medallion architectures.
• Proficiency with Python or PySpark for ingestion and transformation.
• Experience integrating REST APIs, SFTP feeds, SaaS connectors, and partner files.
• Strong understanding of dimensional modeling (Kimball), conformed dimensions, and data mart design.
• Familiarity with CI/CD workflows (Azure DevOps, Git).
• Excellent troubleshooting, debugging, and performance optimization abilities.
• Ability to work in a fast-paced, dynamic environment and manage multiple priorities
• 3-5 years of experience with SSMS / SSDT / SSIS / SSAS / SSRS.

Preferred Skills

• Experience in retail or QSR (Quick Service Restaurant) data ecosystems.
• Experience with POS, labor, inventory, marketing, or supply chain data.
• Experience with Power BI (understanding semantic models and performance considerations).
• Exposure to Azure Data Factory, Synapse, or Databricks.
• Experience with workflow orchestration and metadata-driven frameworks.
• Knowledge of data governance tools (Purview), data security best practices, and lineage management.

Strong written communication skills for documentation and cross-functional alignment.

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Pay: ₹609,000.00 - ₹1,100,000.00 per year

Benefits:

• Commuter assistance
• Work from home

Application Question(s):

• What is your current CTC ?
• Are you willing to work in US EST Timezone ?

Experience:

• Data Engineering: 5 years (Required)
• Pyspark: 3 years (Required)
• Microsoft Fabirc: 3 years (Required)

Shift availability:

• Night Shift (Required)

Work Location: Remote