Senior Data Engineer

Category: IT Services Location: We are seeking a Senior Data Engineer to support the ingestion, processing, and synchronization of data across our analytics platform. This role focuses on using Python Notebooks to ingest data via APIs into Microsoft Fabric's Data Lake and Data Warehouse, with some data being synced to a Synapse Analytics database for broader reporting needs.

The ideal candidate will have hands-on experience working with API-based data ingestion and modern data architectures, including implementing Medallion layer architecture (Bronze, Silver, Gold) for optimal data organization and quality management, with bonus points for exposure to marketing APIs like Google Ads, Google Business Profile, and Google Analytics 4.

This is a remote position. We welcome applicants globally, but this role has a preference for LATAM candidates to ensure smoother collaboration with our existing team

Key Responsibilities

Build and maintain Python Notebooks to ingest data from third-party APIs

Design and implement Medallion layer architecture (Bronze, Silver, Gold) for structured data organization and progressive data refinement

Store and manage data within Microsoft Fabric's Data Lake and Warehouse using delta parquet file formats

Set up data pipelines and sync key datasets to Azure Synapse Analytics

Develop PySpark-based data transformation processes across Bronze, Silver, and Gold layers

Collaborate with developers, analysts, and stakeholders to ensure data availability and accuracy

Monitor, test, and optimize data flows for reliability and performance

Document processes and contribute to best practices for data ingestion and transformation

Tech Stack You'll Use Ingestion & Processing:

Python (Notebooks)

PySpark

Storage & Warehousing:

Microsoft Fabric Data Lake & Data Warehouse

Delta Parquet files

Sync & Reporting: Azure Synapse Analytics Cloud & Tooling: Azure Data Factory, Azure DevOps Requirements Strongexperience with Python for data ingestion and transformation

Proficiencywith PySpark for large-scale data processing;

Proficiencyin working with RESTful APIs and handling large datasets;

Experiencewith Microsoft Fabric or similar modern data platforms;

Understandingof Medallion architecture (Bronze, Silver, Gold layers) and data lakehouseconcepts;

Experienceworking with Delta Lake and parquet file formats;

Understandingof data warehousing concepts and performance tuning;

Familiaritywith cloud-based workflows, especially within the Azure ecosystem.

Nice toHave Experiencewith marketing APIs such as Google Ads or Google Analytics 4;

Familiaritywith Azure Synapse and Data Factory pipeline design;

Understandingof data modeling for analytics and reporting use cases;

Experiencewith AI coding tools;

Experiencewith Fivetran, Aribyte, and Riverly.

Details Originally posted on Himalayas