Senior Data Engineer

This is a fully remote position, open to applicants in Argentina.

📋 Description

• Design and set up the Microsoft Fabric workspace architecture for development, staging, and production environments.

• Establish and implement the OneLake structure, storage methodologies, and capacity planning.

• Develop Bronze landing zone standards, which include: Parquet/Delta formats, partitioning strategies, schema-on-read patterns, and raw payload preservation.

• Construct and oversee Data Factory pipelines, encompassing: scheduling protocols, dependency mappings, and backfill procedures.

• Set up and sustain native Microsoft connectors for essential business systems (for instance, Salesforce, Dataverse, and comparable platforms).

• Define and document extraction specifications for approximately 24 operational systems on a per-source basis.

• Collaborate with downstream analytics stakeholders to establish the Bronze-to-Silver/warehouse consumption agreement.

• Oversee schema evolution, time-travel configurations, and strategies for table optimization and retention.

• Generate as-built documentation, handoff materials, runbooks, and architectural references.

• Conduct an audit of the existing Fabric tenant and ingestion setup during the project's initial phase.

⛳️ Requirements

• Over 7 years of experience in data engineering.

• More than 2 years of direct experience with Microsoft Fabric (or equivalent lakehouse platform ownership, though Fabric experience is highly preferred).

• Strong background in building and managing data ingestion pipelines and warehouse landing zones.

• Profound understanding of medallion architecture, particularly in designing the Bronze/landing layer.

• Advanced knowledge of Delta Lake/Parquet, schema evolution, partitioning, time travel, and maintenance patterns such as OPTIMIZE/VACUUM.

• Experience with CDC/change data capture methodologies from systems like SQL Server, PostgreSQL, or similar event/change-streaming frameworks.

• Expert-level SQL proficiency, including T-SQL and Spark SQL.

• Strong comprehension of data warehouse schema design, naming conventions, and data contract frameworks.

• Capability to produce clear technical documentation, including ingestion specifications, architecture diagrams, handoff documents, and runbooks.

🏝️ Benefits

• Competitive salary and performance bonuses.

• Comprehensive health and wellness benefits.

• Opportunities for professional development and training.

• Flexible work arrangements and a supportive team environment.