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Data Engineering Analyst
Marsh McLennan. Collaborate with stakeholders to understand data requirements and translate them into technical specifications .
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in designing and implementing data pipelines and ETL processes, with a strong proficiency in Python and SQL. Capable of managing cross-functional teams and ensuring data quality through thorough testing and documentation.
Highest-signal resume keywords
Data Pipeline DevelopmentETL And ELT ConceptsPython ProficiencySQL ProficiencyDatabricks Familiarity
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 ModelingDatabase DesignAPI IntegrationData IngestionFunctional TestingAutomated TestingData Quality ChecksDocumentation ProceduresAWS ExperienceAzure Experience
Soft Skills
CollaborationStakeholder EngagementTeam Management
Tools & Technologies
Apache SparkDatabricksSnowflake
Industry Keywords
Data EngineeringData ScienceInformation Technology
Tech Stack
Tools & technologiesApacheAWSAzureETLPythonSparkSQL
About the role
Key responsibilities & impact- Collaborate with stakeholders to understand data requirements and translate them into technical specifications
- Design, develop, and implement data pipelines and ETL processes
- Perform thorough unit testing to validate functionality and performance
- Implement data quality checks and validation processes
- Coordinate with cross-functional teams on project goals, timelines, and deliverables
- Monitor data workflows and pipelines for performance, reliability, and efficiency
- Implement improvements as necessary
- Create and maintain documentation for data processes, architecture, and workflows
- Conceptualize and implement the setup and management of the Databricks-based data platform across different regions
Requirements
What you’ll need- Bachelor’s degree in computer science, Data Science, Information Technology, or a related field
- Proficiency in Python and SQL
- Experience in data modeling and database design
- 5+ years of experience working as a Data Engineer
- Strong understanding of ETL and ELT concepts
- Experience with API integration and data ingestion from various sources
- Experience with functional and automated data testing
- Knowledge of proper documentation procedures and automation principles
- Familiarity with Apache Spark
- Experience with AWS or Azure
- Experience with AI integration on test environments
- Ability to manage QA Engineers and guide through SCRUM calls
- Familiarity with Databricks and Snowflake
Benefits
Comp & perks- Professional development opportunities
- Interesting work
- Supportive leaders
- Vibrant and inclusive culture
- Flexible work environment
- Benefits and rewards to enhance well-being
- Flexibility of working remotely
- Collaboration, connections and professional development benefits from working in the office
- Accommodation support for needs requiring it