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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, architecture, and cloud-based data platforms, with a strong focus on building and leading high-performing teams. Proficient in defining data strategies, implementing scalable data solutions, and ensuring data quality and governance.
Highest-signal resume keywords
Data EngineeringPeople ManagementSQL ProficiencyAWS Cloud InfrastructureData 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
Data EngineeringData ArchitectureSQLPythonRelational Database DesignData Processing PipelinesCloud Data PlatformsData GovernancePerformance TuningData Modeling
Soft Skills
CommunicationStakeholder ManagementTeam Leadership
Tools & Technologies
AWS RedshiftSnowflakeDatabricksGitHubKafkaAirflowS3GlueSageMakerBedrock
Industry Keywords
Data StrategyData VisionData EcosystemEngineering StandardsScalable Solutions
Tech Stack
Tools & technologiesAirflowAmazon RedshiftAWSCloudDistributed SystemsKafkaPythonSQL
About the role
Key responsibilities & impact- Lead the transformation of data from a reporting and analytics function into a strategic product capability
- Define and drive the company’s data vision, strategy, and roadmap
- Build, lead, and develop the data organization across data engineering, analytics, and data science
- Manage and develop a high-performing team of nine
- Partner with cross-functional leaders to translate company objectives into scalable data solutions, platforms, and insights
- Shape the technical direction of the data platform with the Staff Data Engineer
- Contribute to architecture, design, and implementation of critical systems and solutions
- Establish engineering standards, best practices, and design patterns across the data ecosystem
- Drive data modeling, quality, governance, security, observability, and validation practices
- Lead the design, implementation, and operation of AWS cloud-based data infrastructure and services
- Prioritize investments in data platforms, tooling, and processes
- Influence company-wide technology strategy as a member of the engineering leadership team
Requirements
What you’ll need- 7+ years of experience in data engineering, software engineering, data platforms, or related technical disciplines
- 3+ years of people management experience, including hiring, performance management, coaching, and career development
- Experience defining data architecture, platform strategy, and engineering standards
- Strong proficiency with SQL and relational database design, optimization, and performance tuning
- Strong software engineering fundamentals and hands-on production systems experience with Python and other modern programming languages
- Expertise with modern cloud data platforms and warehouses such as Snowflake, Amazon Redshift, Databricks, or similar
- Experience designing, building, and operating scalable batch and real-time or near-real-time data processing pipelines
- Experience using GitHub or similar source control platforms in collaborative, distributed engineering teams
- Excellent communication and stakeholder management skills
- Bachelor's degree in Computer Science, Engineering, Information Systems, or a related technical field, or equivalent practical experience
- Preferred: experience building data products or data-driven features serving as competitive differentiators or revenue drivers
- Preferred: hands-on experience with AWS tools including Redshift, S3, MSK, Glue, SageMaker, and Bedrock
- Preferred: experience with Kafka, dbt, and data orchestration tools such as Airflow or Dagster
- Preferred: experience with batch and near-real-time data processing pipelines
- Preferred: experience designing and implementing scalable distributed systems
- Must reside in an eligible U.S. state and be legally authorized to work in the United States
Benefits
Comp & perks- Flexible work environment
- Remote work available across eligible U.S. states
- Significant autonomy, ownership, and visibility
- Opportunity to build and scale the data platform, organization, and culture
- Opportunity to expand the team and develop future leaders