Senior Data Engineer

What You’ll Do

Architect and optimize high-performance data pipelines for structured and unstructured data.
Design scalable ETL workflows that fuel our AI/ML models and business intelligence systems. Engineer cloud-native data infrastructure on AWS, GCP, or Azure to handle massive datasets.
Build and maintain data lakes, warehouses, and real-time data streaming solutions.
Optimize query performance and database architectures for lightning-fast insights.
Automate workflows using orchestration tools like Airflow, Luigi, or Prefect.
Collaborate with data scientists, analysts, and engineers to unlock the full potential of data.
Security & Compliance – Ensure AI solutions comply with industry standards and data privacy regulations.

What Makes You a Great Fit?

3-7 years of hands-on experience in data engineering or a related field.
Strong expertise in Python, SQL, and distributed data frameworks (Spark, Hadoop, Kafka).
Deep understanding of data modeling, warehousing (Snowflake, Redshift, BigQuery), and schema design.
Experience with both relational and NoSQL databases (PostgreSQL, MySQL, MongoDB, Cassandra).
Solid knowledge of real-time and batch data processing (Kafka, Flink, Spark Streaming).
Passion for automation, CI/CD, and infrastructure-as-code (Terraform, Docker, Kubernetes).
Ability to troubleshoot and optimize complex data workflows.
A problem-solving mindset with a love for tackling large-scale data challenges.