Senior Manager Data Engineering

Mid / Senior


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About This Workplace

Meytier Partner

Publicis Sapient is looking for a hands-on Senior Manager to join our team of bright thinkers and doers. You’ll use your problem-solving creativity to design, architect, and develop high-end technology solutions that solve our clients’ most complex and challenging problems across different industries. We are on a mission to transform the world, and you will be instrumental in shaping how we do it with your ideas, thoughts, and solutions.

Key Responsibilities:

  • Develop, design, and implement consumer data models based on business requirements and objectives.
  • Collaborate with various stakeholders, such as business analysts, architects, and developers, to understand data needs and convert these needs into effective data models.
  • Evaluate and optimize existing data models for improvement.
  • Ensure that data models adhere to industry best practices, standards, and guidelines.
  • Conduct data profiling and analysis to identify data quality issues and propose data cleansing and remediation strategies.
  • Collaborate with database administrators to optimize database performance and maintain data integrity.
  • Work closely with ETL developers to integrate data models into data integration processes.
  • Stay updated on the latest trends and technologies in data modeling, cloud computing, and database design.
  • Mentor, support and manage team members

Desired Profile:

  • Demonstrable experience in enterprise level data platforms involving implementation of end-to-end data pipelines 
  • Hands-on experience with at least one of the leading public cloud data platforms (Amazon Web Services, Azure or Google Cloud)  
  • Experience with column-oriented database technologies (e.g., Big Query, Redshift, Vertica), NoSQL database technologies (e.g., DynamoDB, BigTable, Cosmos DB, etc.) and traditional database systems (e.g., SQL Server, Oracle, MySQL)
  • Experience in architecting data pipelines and solutions for both streaming and batch integrations using tools/frameworks like Glue ETL, Lambda, Google Cloud DataFlow, Azure Data Factory, Spark, Spark Streaming, etc. 
  • Metadata definition and management via data catalogs, service catalogs, and stewardship tools such as OpenMetadata, DataHub, Alation, AWS Glue Catalog, Google Data Catalog.
  • Test plan creation and test programming using automated testing frameworks, data validation and quality frameworks, and data lineage frameworks
  • Data modeling, querying, and optimization for relational, NoSQL, timeseries, graph databases, data warehouses and data lakes
  • Data processing programming using SQL, DBT, Python, and similar tools
  • Logical programming in Python, Spark, PySpark, Java, Javascript, and/or Scala
  • Cloud-native data platform design with a focus on streaming and event-driven architectures
  • Participate in integrated validation and analysis sessions of components and subsystems on production servers
  • Data ingest, validation, and enrichment pipeline design and implementation
  • SDLC optimization across workstreams within a solution
  • Bachelor’s degree in Computer Science, Engineering, or related field

Compensation Range: $129k- $252k

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