XX
Senior Data EngineereTeamUnited States

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XX

Senior Data Engineer

eTeam
  • US
    United States
  • US
    United States

Über

Performance Expectations:
Technical Hiring Criteria (Must Haves) • Top 3 Required skills: Spark, Scala, SQL • Years of experience in each of the must-have skills: 7+ Years • Any Certifications required: No
Any additional information you would like to share about the project specs/nature of work: NA
Role : Software Engineer - Data We are seeking a highly experienced Engineer to join our team and own the development of a Tiered data architecture for our data. In this role, they would be responsible for crafting and building a comprehensive data architecture that will enable seamless data integration and enable the delivery of high-quality insights to our leadership and business stakeholders.Skills Required ??: Apache Spark, SQL, git, Programing Language (Python, Java, Scala) Nice to have ??: Understanding of Design Patterns, Able to discuss tradeoffs between RDBMS vs Distributed StorageKey Qualifications - Proven experience in data engineering, data architecture, or a related field - Experience in building and deploying tiered data architecture for analytics data is a plus - Strong understanding of data modeling, data warehousing, and ETL concepts - Proficiency in SQL and experience with at least one major data analytics platform, such as Hadoop or Spark - Experience with data orchestration tools like Airflow is a nice to have - Excellent problem-solving and analytical skills, and the ability to work well under tight deadlines - Excellent interpersonal skills and the ability to collaborate effectively with cross-functional teamsDescription - Design and implement a tiered data architecture that integrates analytics data from multiple sources in an efficient and effective manner. - Develop data models and mapping rules to transform raw data into actionable insights and reports. - Collaborate with the analytics and business teams to understand their requirements and deliver solutions that meet their needs. - Ensure data quality and accuracy by developing data validation and reconciliation processes. - Play an active role in the development and maintenance of user documentation, including data models, mapping rules, and data dictionaries. - Collaborate with multi-functional teams to define and implement data governance policies and standards. - Stay informed about the latest developments in data analytics and data management technologies and recommend new tools and methodologies to improve the semantic layer.
  • United States

Sprachkenntnisse

  • English
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