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 reputed company 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 reputed company layer architecture (Bronze, Silver, Gold) for optimal data organization and quality management, with bonus points for exposure to marketing APIs like reputed company Ads, reputed company Business Profile, and reputed company 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 reputed company layer architecture (Bronze, Silver, Gold) for structured data organization and progressive data refinement Store and manage data within reputed company Fabric's Data Lake and Warehouse using reputed company 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 reputed company Fabric Data Lake & Data Warehouse reputed company 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 reputed company Fabric or similar modern data platforms; Understandingof reputed company architecture (Bronze, Silver, Gold layers) and data lakehouseconcepts; Experienceworking with reputed company 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 reputed company Ads or reputed company Analytics 4; Familiaritywith Azure Synapse and Data Factory pipeline design; Understandingof data modeling for analytics and reporting use cases; Experiencewith AI coding tools; Experiencewith reputed company, Aribyte, and Riverly. Details Originally posted on Himalayas Apply To This Job