Data Engineer

Job Description for Data Engineer

What is Farmdar?

Farmdar is an agritech company using AI and space technologies at scale for sustainable agriculture and climate adaptation. Our products—CropScan, YieldPro, and AgriChain—deliver actionable insights to farmers and agribusinesses, helping them increase yields, reduce input costs, and build climate resilience. Our mission is to become the world’s most trusted crop insights platform.

Job Title: Data Engineer

Job Type: Permanent

Location: Lahore - Hybrid

Role Overview:

We are seeking a Data Engineer with strong Python expertise to design, build, and maintain scalable data pipelines and geospatial analytics infrastructure. You'll architect and optimize complex ETL workflows using Apache Airflow, process large-scale geospatial datasets, and build robust data systems that power our analytics and mapping platforms. This role combines hands-on data engineering with infrastructure knowledge to deliver reliable, high-performance data solutions.

Responsibilities:

• Data Pipeline Development: Design, build, and maintain production-grade ETL/ELT pipelines using Apache Airflow and Python for processing structured, unstructured, and geospatial data
• Geospatial Data Engineering: Develop spatial ETL workflows for processing GIS data, satellite imagery, vector tiles, and geospatial analytics at scale
• Workflow Orchestration: Create and optimize complex Airflow DAGs for data ingestion, transformation, quality validation, and delivery
• Data Modeling: Design efficient data models and schemas for analytics, reporting, and geospatial applications across data warehouses and spatial databases
• Python Development: Build reusable data processing frameworks, libraries, and tools using Python (pandas, GeoPandas, GDAL, shapely, etc.)
• Data Quality & Monitoring: Implement data validation, quality checks, monitoring, and alerting for pipeline reliability
• Performance Optimization: Optimize queries, transformations, and processing jobs for performance and cost efficiency
• Infrastructure Support: Deploy and manage data infrastructure components using Docker, Kubernetes, and cloud services
• Collaboration: Partner with analysts, scientists, and engineers to understand requirements and deliver data solutions
• Documentation: Create comprehensive documentation for pipelines, data models, and processes

Requirements:

• Experience: 1+ years in data engineering roles building production data pipelines
• Python Expertise: Advanced Python programming skills with experience in data processing libraries (pandas, NumPy, SQL libraries)
• Apache Airflow: Strong hands-on experience developing, deploying, and managing Airflow for complex workflow orchestration and DAG development
• SQL Proficiency: Expert-level SQL for data transformation, optimization, and analytics
• Geospatial Processing: Experience with geospatial data formats (GeoJSON, Shapefile, GeoTIFF), tools (GDAL, GeoPandas, PostGIS), and spatial analysis
• Data Warehousing: Working knowledge of modern data warehouses (Snowflake, BigQuery, Redshift) and analytics platforms
• ETL Best Practices: Deep understanding of data pipeline patterns, incremental processing, idempotency, and error handling
• Cloud Platforms: Experience with AWS or GCP data services (S3, RDS, BigQuery, Cloud Storage, etc.)
• Version Control: Proficiency with Git and collaborative development workflows
• Problem Solving: Strong analytical and troubleshooting skills for complex data challenges

Nice to Have:

• Advanced GIS: Experience with GeoServer, tile servers, spatial indexing, and map rendering pipelines
• Containerization: Familiarity with Docker and Kubernetes for deploying data applications
• Real-time Processing: Experience with streaming frameworks (Kafka, Flink, Spark Streaming)
• CI/CD: Understanding of automated testing and deployment for data pipelines (GitHub Actions, Jenkins)
• Infrastructure as Code: Exposure to Terraform or CloudFormation
• Scripting: Additional languages like Bash or R for automation and analysis
• Data Governance: Knowledge of data cataloging, lineage tracking, and metadata management

Equal Opportunity Provider:

At Farmdar, we believe in creating an environment where everyone has an equal chance to contribute, grow, and succeed. We want all colleagues to feel welcome and comfortable in the workspace. We discourage discrimination of any kind and encourage respect among our fellow colleagues. Our recruitment process is fair for all, regardless of race, age, gender, color, religion, social status, disability or ethnicity.