Data Engineer

Job Overview

 We’re looking for a skilled and motivated Data Engineer to build and maintain robust, scalable data infrastructure for geospatial and time-series datasets.

 You’ll design efficient databases, develop ETL/ELT pipelines, and ensure high-performance data access for multiple users and applications.

 Key Responsibilities

 • Build and maintain scalable ETL/ELT pipelines for geospatial and time-series data.

 • Design and optimize databases (PostgreSQL/PostGIS, TimescaleDB, InfluxDB, or NoSQL) for efficient storage and querying.

 • Identify and fix performance bottlenecks to support real-time analytical workloads.

 • Develop effective data models ensuring quality, integrity, and accessibility.

 • Monitor and maintain the data platform for stability, security, and scalability.

 • Collaborate with data scientists, analysts, and engineers to deliver reliable solutions.

Required Qualifications

 • 2+ years of experience as a Data Engineer in large-scale production environments.

 • Strong geospatial data knowledge (PostGIS, GeoServer, projections, spatial indexing).

 • Experience managing time-series data (InfluxDB, TimescaleDB, etc.).

 • Proficiency in Python for scripting and data pipeline orchestration.

 • Advanced SQL and database design/optimization skills.

 • Experience with cloud platforms (AWS, Azure, GCP) and orchestration tools (Airflow, Prefect, Dagster).

 • Ability to design scalable systems handling large, fast-moving data.

 Desirable Skills

 • Experience with streaming technologies (Kafka, Kinesis).

 • Knowledge of geospatial formats (GeoJSON, Shapefile, Parquet).

 • Familiarity with Docker or Kubernetes.

 • Experience with data warehouses (Snowflake, BigQuery, Redshift).