Remote job
Data Engineer
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About this role
Role overview Build and operate the data pipelines and models that supply analytics and AI systems with dependable, traceable data. The role spans ingestion, transformation, warehouse design, streaming, and dataset preparation, with quality controls and auditability built into production workflows.
Responsibilities - Develop and run batch and streaming ETL/ELT pipelines using Python and SQL. - Maintain dimensional and analytical warehouse models in dbt, with versioned transformations, tests, documentation, and lineage. - Add validation, freshness checks, and anomaly monitoring to catch and isolate problematic data before it reaches dashboards or models. - Prepare curated, deduplicated, and labeled data for retrieval augmented generation, embeddings, and fine tuning while preserving provenance. - Reconcile real time and batch feeds, and improve query, partitioning, and storage performance in PostgreSQL and cloud warehouses. - Document pipelines and provide observability, reproducibility, and recovery mechanisms.
Requirements - A record of delivering production data pipelines used by other teams. - Strong Python and advanced SQL skills, including query performance and data modeling. - Experience building and maintaining dbt projects and modern warehouse schemas with tests and documentation. - Experience operating an orchestrator such as Airflow, Dagster, or Prefect, including scheduling, retries, and backfills. - Familiarity with AWS, GCP, or Azure data services. - A careful approach to correctness, data lineage, and auditability.
Nice to have - Real time processing experience with Kafka, Kinesis, or Flink. - Dataset preparation for AI workflows, including labeling and deduplication. - Docker, Kubernetes, or Terraform experience; familiarity with data catalogs, PII handling, or compliance controls.
Benefits and work setup - Fully remote within Pakistan, with collaboration centered around Lahore. - A budget for learning, courses, certifications, and conferences. - A defined path toward data architecture or platform leadership.