| Mid (5-7 Years) |
|---|
| Work Location Expectations | |
| Hybrid |
|---|
Summary: Develops scripts, processes, and tools to ingest, transform, and deliver data in a MS Fabric environment to support analytics and reporting needs.
Lakehouse Architecture & Platform Engineering
Design, build, and maintain scalable lakehouse architecture in Microsoft Fabric and OneLake
Ensure high availability, reliability, and performance of data platforms
Data Pipelines & Ingestion
Build and maintain end-to-end data pipelines for ingestion, transformation, and serving
Develop scalable ingestion frameworks for batch and real-time sources (APIs, databases, event streams)
Integrate enterprise systems (Jira, ERP, CRM, flat files, streaming sources)
Data Processing & Transformation
Develop and execute large-scale Spark jobs (batch and streaming)
Author and maintain notebooks (PySpark, SQL) for transformation and analysis
Implement data cleansing, enrichment, and transformation logic
Data Quality & Integration
Build ingestion logic for structured, semi-structured, and unstructured data
Implement data validation and quality controls
Data Enablement
Deliver analytics-ready datasets for Power BI and downstream consumption
Skill Requirements
Microsoft Fabric (Lakehouse, OneLake, Pipelines, Notebooks)
Apache Spark (PySpark, Spark SQL)
SQL
Python
Delta Lake / Delta Tables
Data Pipeline Design (ETL / ELT)
API & Streaming Data Integration
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