Data Engineer

We are seeking a Data Engineer to join our growing data team to design, build, and maintain data pipelines and infrastructure. You will work on distributed systems, orchestration frameworks, cloud environments, and modern data technologies to ensure that data flows reliably and efficiently across the organization.Key Responsibilities:Optimize processes for scalability and efficiency in distributed environments.Ensure data quality, integrity, and performance across workflows.Work with cloud-native solutions and containerized environments (Docker/Kubernetes).Implement and manage orchestration frameworks (Airflow/Dagster/etc.).Collaborate with cross-functional teams to support business and research needs.Develop and enforce CI/CD processes and data testing frameworks (pytest, GE, or similar).Monitor, troubleshoot, and continuously improve pipeline reliability and performance.Requirements: Youll be a great fit if you have4+ years of professional experience with Python and SQL.Proven experience building and maintaining ETL/ELT pipelines (batch/streaming) with orchestration frameworks (Airflow, Dagster, or similar).Hands-on experience with distributed computing frameworks (Spark, Dask, Beam) and large-scale data processing.Experience with major cloud platforms (AWS, GCP, or Azure); GCP/BigQuery is an advantage.Proficiency with Docker/Kubernetes and CI/CD pipelines (GitLab CI, GitHub Actions, or similar).Solid understanding of software engineering practices (data structures, algorithms, TDD, code quality).Familiarity with data testing and monitoring frameworks (pytest, Great Expectations, observability tools).Nice to Have:Experience with dbt, ClickHouse, or Ray.Familiarity with Python data libraries (pandas, NumPy, Apache Arrow, Jinja).Background in functional programming.This position is open to all candidates.