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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in building and optimizing data platforms, with a strong focus on ETL/ELT processes, data governance, and quality assurance. Proficient in SQL, Python, and data lake architectures, ensuring effective collaboration with cross-functional teams to meet data needs.
Highest-signal resume keywords
Data EngineeringETL/ELT Pipeline DevelopmentSQL ProficiencyData Lakehouse ArchitectureMicroservices Architecture
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
SQLPythonData ModelingETL/ELT ProcessesApache IcebergClickHouseApache SparkData GovernanceData QualityMicroservices
Soft Skills
Strong Multitasking SkillsTeam PlayerExcellent Communication Skills
Tools & Technologies
TemporalAWSS3DockerKubernetesCI/CDBI ToolsAirflowAWS EMRAI-Assisted Development Tools
Industry Keywords
Data InfrastructureData ProcessingBatch Data ProcessingData OrchestrationCloud Environments
Tech Stack
Tools & technologiesAirflowApacheAWSCloudDockerETLJavaKubernetesMicroservicesPythonScalaSparkSQLTableau
About the role
Key responsibilities & impact- Develop a scalable data platform integrating multiple sources for easy access
- Design and enhance data tools for orchestration, governance, Data-Lakehouse, BI, and related functions
- Ensure smooth operation of data systems for analysts, scientists, and engineers
- Optimize data pipelines for ingestion, processing, and output in a microservices environment
- Build, maintain, and monitor ETL/ELT processes and orchestrate workflows using Temporal
- Troubleshoot and improve the performance, scalability, and reliability of data infrastructure including S3, Apache Iceberg, and ClickHouse
- Collaborate cross-functionally with data scientists, analysts, and backend engineers to understand data needs and deliver solutions
- Implement and champion data quality, governance, and security best practices across the platform
Requirements
What you’ll need- 3+ years of experience as a Data Engineer or in a similar data infrastructure role
- Strong proficiency in SQL and hands-on experience with data modeling
- Experience with data lake/lakehouse architectures (e.g., Apache Iceberg, S3, or similar)
- Experience with analytical / columnar databases (e.g., ClickHouse or similar)
- Experience building and orchestrating ETL/ELT pipelines (e.g., Temporal, Airflow, or similar)
- Strong programming skills in Python and/or Scala/Java
- Experience working within a microservices architecture and cloud environments (AWS preferred)
- Self-motivated, strong multitasking skills, and a demonstrated team player
- Excellent communication skills and the ability to work both independently and collaboratively
- Hands-on experience with Apache Spark (or similar technologies) for large-scale data processing
- Professional proficiency in written and spoken English
- Role focused on batch data processing, not real-time streaming
- Nice to have: Experience contributing to open-source data platforms and tools
- Nice to have: Familiarity with BI and visualization tools (e.g., Superset, Looker, Tableau, Metabase, or similar)
- Nice to have: Experience with containerization and orchestration (Docker, Kubernetes)
- Nice to have: Experience with infrastructure-as-code and CI/CD practices
- Nice to have: Experience with AWS EMR and running Apache Spark workloads in a cloud environment
- Nice to have: Experience leveraging AI-assisted development tools (e.g., GitHub Copilot, Cursor, or similar)
Benefits
Comp & perks- Remote work
- Full-time employment