Senior Data Engineer

• Build & optimize a high performance data platforms that powering analytics, dashboards, and AI models
• Pioneer team to freeing Data Scientists & Analysts team from manual engineering
• Salary up to $9,000 + AWS + Bonus

We're hiring Senior Data Engineer to champion automation, scalability, and best practices that accelerate company's data and AI maturity.

Key Responsibilities:

1. Design, build, and maintain scalable, end-to-end pipelines for data ingestion, transformation, and delivery.
2. Automate ETL/ELT workflows (Airflow, Glu, Step Functions, Prefect) to eliminate manual intervention and improve reliability.
3. Implement validation, version control, and rollback mechanisms for reliability and traceability.
4. Build self-healing, auto-scaling pipelines ensuring near-zero downtime and operational resilience.
5. Develop and optimize lakehouse & warehouse architectures using Databricks, Snowflake, Redshift, S3, EMR, Glue, and Lake Formation.
6. Integrate monitoring, alerting, and logging (CloudWatch, Prometheus, Grafana) for proactive issue resolution.
7. Build data foundations for forecasting, segmentation, retention, and KPI decomposition models.
8. Create reusable feature stores, model registries, and tracking frameworks supporting the MLOps lifecycle.
9. Enable AI-assisted analytics through natural language query, LLM integration, and automated insights.
10. Partner with cross-functional teams to ensure data readiness aligns with business timelines.

Requirements:

• min. Degree in Computer Science, Information Systems, or related field
• min. 6 years & above in data engineering, pipeline design, or infrastructure operations
• Expert in SQL, Python and frameworks such as Spark, Hadoop, dbt, and Airflow
• Strong knowledge of AWS stack such as Redshift, Glue, S3, EMR, Athena, Lambda, Lake Formation
• Familiar with Databricks, Snowflake, and MLOps tools (SageMaker, MLflow, Vertex AI)
• Skilled in data modelling, performance tuning, and cost optimization