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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in Data Engineering and Data Infrastructure, with a strong focus on SQL, data modeling, and building scalable ETL/ELT systems. Proficient in developing reusable data engineering tools and frameworks while ensuring data governance and lifecycle management.
Highest-signal resume keywords
Data EngineeringSQL ExpertiseETL/ELT SystemsData GovernanceCloud Infrastructure
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Data ModelingETLELTData ProcessingData QualityData TransformationData ArchitectureProgramming (Python, Scala, Java, Go)Data IngestionData Lifecycle Management
Tools & Technologies
DbtAirflowSparkSnowflakeDatabricksBigQueryRedshiftKafkaFlinkKubernetes
Industry Keywords
Data LakeData WarehouseGDPRData GovernanceData LineagePII HandlingSchema ManagementIncremental ProcessingMonitoringAlerting
Tech Stack
Tools & technologiesAirflowAmazon RedshiftAWSAzureBigQueryCloudETLGoogle Cloud PlatformJavaKafkaKubernetesPythonScalaSparkSQLGo
About the role
Key responsibilities & impact- Design, build, and operate foundational data systems and shared data assets for analytical, operational, and business use cases
- Build and evolve scalable data ingestion and transformation frameworks across the data lake and data warehouse
- Develop reusable data engineering tools and abstractions, including dbt-related frameworks and capabilities
- Design durable domain data models for core business domains such as users, subscriptions, and activities
- Build workflows supporting data governance, privacy, GDPR-related deletion, retention, access, and data lifecycle management
- Improve data platform reliability and observability through testing, data quality checks, lineage, monitoring, alerting, and operational tooling
- Optimize large-scale data processing and storage for performance, maintainability, scalability, and cost
- Partner with data engineering, analytics engineering, software engineering, data science, security, privacy, and infrastructure teams
- Establish scalable data architecture and engineering standards
Requirements
What you’ll need- 3–5+ years of professional experience in Data Engineering, Data Infrastructure, Software Engineering, or a related field
- Experience owning production data systems
- Strong expertise in SQL and data modeling
- Experience with dimensional, normalized, or domain-oriented data models for large-scale analytical systems
- Experience building and operating ETL/ELT and data processing systems using dbt, Airflow, Spark, or similar frameworks
- Experience developing reusable tooling, frameworks, or abstractions for data pipelines and transformations
- Proficiency in at least one general-purpose programming language such as Python, Scala, Java, or Go
- Understanding of modern data warehouse and data lake architectures
- Experience with technologies such as Snowflake, Databricks, BigQuery, Redshift, Iceberg, Delta Lake, or similar systems
- Experience processing and transforming large datasets, including schema evolution, data normalization, deduplication, backfills, incremental processing, and data quality
- Understanding of data governance and data lifecycle concepts including lineage, retention, deletion, access control, PII handling, and GDPR/privacy requirements
- Experience implementing production-grade data quality, monitoring, alerting, testing, and observability
- Ability to independently reason about data architecture and make sound technical decisions
- Comfort working with cloud infrastructure such as AWS, GCP, or Azure
- Experience with Kafka, Flink, Kubernetes, open table formats, data catalogs and lineage systems, schema management, CDC, or internal developer platforms is a plus
Benefits
Comp & perks- Equity
- Benefits and total rewards programs
- Reasonable accommodation for candidates with disabilities
- Inclusive workplace where employees can grow and thrive