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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in designing and implementing scalable ETL/ELT pipelines and cloud data architectures, with a strong focus on data modeling, performance tuning, and collaboration with cross-functional teams. Proficient in ensuring data integrity and optimizing workflows in high-velocity environments.
Highest-signal resume keywords
ETL/ELT Pipeline DesignCloud Data WarehousingSpark and AirflowSQL Performance TuningData Modeling (Star Schema, Data Vault)
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
ETL/ELT Pipeline ImplementationCloud Data WarehousingSQL Performance TuningData ModelingPythonScalaSparkAirflowKafkaDbt
Soft Skills
Autonomous TroubleshootingMentoring
Tools & Technologies
SnowflakeDatabricksBigQueryRedshiftAWSAzureGCP
Industry Keywords
Data EngineeringData IngestionData TransformationData ProcessingBusiness IntelligenceData IntegrityWorkflow Optimization
Tech Stack
Tools & technologiesAirflowAmazon RedshiftAWSAzureBigQueryCloudETLGoogle Cloud PlatformKafkaPythonScalaSnowflakeSparkSQLVault
About the role
Key responsibilities & impact- Lead the design and implementation of scalable, production-grade ETL/ELT pipelines for large-scale data ingestion, transformation, and processing
- Design and optimize cloud data warehouses, lakes, and lakehouses to support advanced analytics, BI, and reporting workloads
- Implement automated data validation schemas, monitoring frameworks, and testing suites
- Ensure low-latency performance, high data accuracy, and strict security compliance
- Engineer resilient data models using Star Schema, Data Vault 2.0, and Dimensional Modeling
- Tune query performance and storage efficiency
- Partner with Data Scientists, ML Engineers, and Business Analytics stakeholders to translate business objectives into scalable technical data architectures
- Mentor mid-level and junior data engineers
- Establish automated deployment patterns for data pipelines
- Maintain comprehensive architectural documentation
Requirements
What you’ll need- 5+ years of dedicated professional data engineering experience
- Proven track record of architecting distributed data platforms in high-velocity startup or nearshore environments
- Deep hands-on experience with Spark, Airflow, Kafka, dbt, and cloud data warehouses such as Snowflake, Databricks, BigQuery, or Redshift
- Advanced proficiency in Python or Scala
- Expert-level mastery of complex SQL performance tuning and query optimization
- Hands-on experience building enterprise data solutions on AWS, Azure, or GCP
- Deep command of Star Schema and Data Vault data modeling paradigms
- Strong autonomous troubleshooting capabilities
- Passion for data integrity and proactive workflow optimization
- Advanced English fluency, written and spoken, mandatory for direct, real-time collaboration with U.S.-based client teams and stakeholders
Benefits
Comp & perks- USA Contractor / 100% Remote
- Competitive Pay (USD)
- Holidays Off & Paid Time Off
- Health insurance assistance program
- Opportunity to work with high-growth US-based companies and cutting-edge tech stacks
- Agentic AI tools and training
- Coursera Enterprise
- Studio practice labs
- High-touch onboarding
- Transparent leadership communication
- Community recognition
- Psychological safety
- Continuous multi-project pipeline
- Direct engagement with U.S. client teams and roadmaps