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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 ETL development, with a strong focus on building and supporting Data Lakehouse environments. Proficient in Python, PySpark, and cloud platforms, while ensuring data quality and collaborating effectively with cross-functional teams.
Highest-signal resume keywords
Data EngineeringETL DevelopmentData Lakehouse DesignPython and PySparkCloud Platforms (AWS, Azure, GCP)
Tech Stack
Tools & technologiesAbout the role
Key responsibilities & impact- Develop scalable data pipelines and build new integrations to support continued growth in data volume and complexity
- Build a robust Data Lakehouse supporting Vericast's marketing solutions business and financial institution clients
- Support pre-sales, campaign execution, campaign performance analysis, and benchmarking
- Collaborate with AI, Analytics, and business teams to improve data models feeding AI and analytics tools
- Implement processes and systems to monitor data quality and ensure production data availability and accuracy
- Perform data analysis to troubleshoot data-related issues and support resolution
- Provide post-deployment support and quickly resolve unexpected production issues
- Partner with business units and engineering teams to shape long-term data platform architecture strategy
Requirements
What you’ll need- Bachelor's degree in Computer Science, Information Technology, or a related field, with 5+ years of relevant experience; or Master's degree in Computer Science, Information Technology, or a related field (preferred)
- 5+ years of experience in Data Engineering, ETL development, or Data Platform Engineering
- Experience working within a Financial Institution (FI), Banking, FinTech, MarTech, AdTech, Marketing Services, or Marketing Agency environment
- Experience supporting customer, campaign, audience, marketing performance, attribution, advertising, or transactional data at scale
- Strong experience with Python and PySpark for building production-grade data pipelines
- Experience designing, building, and supporting Data Lakehouse environments
- Experience with Apache Airflow, Iceberg, Hive, S3, and Trino
- Experience with cloud platforms such as AWS, Azure, or GCP
- Experience with Agile software development methodologies
- Experience with GitLab and CI/CD processes
- Experience supporting AI and machine learning applications
- Understanding of machine learning models and data requirements for Data Science teams
- Experience with distributed systems and parallel data processing using Spark, PySpark, Hadoop, Kafka, and Hive
- Proficiency with relational databases
- Strong knowledge of Linux/Unix-based systems
- Hands-on experience with Apache Ranger and Rancher/Kubernetes
- Excellent analytical, conceptual, and problem-solving skills
- Strong communication skills that promote cross-team collaboration
Benefits
Comp & perks- Medical coverage
- Dental coverage
- Vision coverage
- 401K
- Generous PTO allowance
- Life insurance
- Employee assistance
- Pet insurance
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 EngineeringETL DevelopmentData Lakehouse DesignPythonPySparkApache AirflowDistributed SystemsRelational DatabasesMachine LearningData Analysis
Soft Skills
Analytical SkillsProblem-Solving SkillsCommunication SkillsCollaboration Skills
Tools & Technologies
Apache AirflowIcebergHiveS3TrinoGitLabCI/CDApache RangerRancherKubernetes
Industry Keywords
Financial InstitutionBankingFinTechMarTechAdTechMarketing ServicesCampaign PerformanceAttributionTransactional DataAgile Methodologies