Data Infrastructure Engineer

Job Description for Data Infrastructure EngineerWhat 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 Infrastructure EngineerJob Type: PermanentLocation: Lahore - HybridRole Overview:We are looking for a Data Infrastructure Engineer to design, maintain, and optimize our cloud infrastructure with a focus on data pipeline orchestration and containerized environments. You'll manage critical data workflows using Apache Airflow while ensuring scalable, secure, and reliable deployments using Kubernetes, Docker, and Helm. This role bridges infrastructure operations with data engineering to support our geospatial and analytics platforms.Responsibilities:Data Pipeline Management: Design, deploy, and maintain Apache Airflow for orchestrating complex data workflows and ETL processesContainer Orchestration: Manage and optimize containerized applications using Kubernetes, Docker, and HelmCI/CD: Design and maintain CI/CD pipelines for automated builds, testing, and deploymentsInfrastructure as Code: Implement IaC practices for environment consistency and repeatabilityMonitoring & Optimization: Monitor system performance, reliability, and cost efficiency across clusters and data pipelinesWorkflow Automation: Build and optimize DAGs for data processing, geospatial ETL, and scheduled tasksTroubleshooting: Debug deployment issues and optimize workloads for scalability and performanceCollaboration: Work with data engineers and developers to streamline delivery pipelines and production operationsSecurity & Compliance: Maintain security, compliance, and access control across environmentsData Operations: Support data infrastructure for analytics, reporting, and geospatial processingRequirements: Experience: 2+ years managing production systems using Kubernetes and DockerAirflow: Hands-on experience with Apache Airflow for workflow orchestration, DAG development, and pipeline managementContainer Orchestration: Proficiency with Helm charts for deployment automation and configuration managementCloud Platforms: Strong understanding of AWS (primary) and GCPCI/CD: Experience with GitHub Actions, Jenkins, or similar toolsMonitoring: Familiarity with monitoring and logging stacks (Prometheus, Grafana, ELK, Airflow monitoring)System Administration: Solid knowledge of networking, security, and Linux system administrationScripting: Proficiency in Python (required for Airflow DAGs), Bash, or GoData Workflows: Understanding of ETL processes, data pipelines, and scheduling patternsNice to Have:GIS Infrastructure: Experience deploying and managing geospatial services (GeoServer, PostGIS, tile servers, GDAL)Exposure to geospatial data processing pipelines and spatial ETL workflowsExperience with Terraform or other IaC toolsKnowledge of data warehousing and analytics platforms (Snowflake, BigQuery, Redshift)Understanding of microservice architectures and cloud-native development workflowsFamiliarity with spatial databases and geospatial data formatsExperience optimizing performance for data-intensive and GIS applicationsBackground in data engineering or analytics engineeringEqual 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