Description
The Data Engineering Sr Manager will be responsible for managing data engineering deliverables to support our technology and product engineering teams as well as the needs of our data scientists and business analysts. This role will be responsible for employing techniques to create and sustain structures that allow for the analysis of data while remaining familiar with dominant programming and deployment strategies in the field.
Job Responsibility
• Manage team of data engineers (both full-time associates and/or third-party resources).
• Lead and participate in architecture and design efforts.
• Lead the building of systems for all parts of the data lifecycle: collection, storage, accessibility, insights, and business action.
• Identify, design, and implement internal process improvements including re-designing infrastructure for scalability, optimizing data delivery, and automating manual processes.
• Build required infrastructure for optimal extraction, transformation, and loading of data from various data sources using Snowflake/Azure and SQL technologies.
• Analyze and organize raw data.
• Build data systems and pipelines.
• Evaluate business needs and objectives.
• Interpret trends and patterns.
• Conduct complex data analysis and report on results.
• Prepare data for prescriptive and predictive modeling.
• Build algorithms and prototypes.
Job Qualifications
• Must be able to communicate ideas and analysis results effectively both verbally and in writing to both internal and external clients.
• Responsible for executing analytical projects, leading project development for data analysis and decision support tools.
• Coordinate closely with the Business Intelligence and DWH team for data integration and alignment.
• Knowledge of programming languages (e.g., Java and Python).
• Hands-on experience with SQL database design.
• Great numerical and analytical skills.
• Degree in Computer Science, IT, or similar field; Master's preferred.
• Data engineering certification (e.g., IBM Certified Data Engineer) is a plus.
• Experience with big data tools: Hadoop, Spark, Kafka, etc.
• Experience with relational SQL and NoSQL databases including Postgres and Cassandra.
• Experience with data pipeline and workflow management tools: Azkaban, Luigi, Airflow, etc.
• Experience with Snowflake/Azure cloud services: EC2, EMR, RDS, Redshift.
• Experience with stream-processing systems: Storm, Spark-Streaming, etc.
• Experience with object-oriented/object function scripting languages: Python, Java, C++, Scala, etc.
Education/Experience
Degree in information technology or computer science with additional vendor-specific certification. BS or MS degree in Computer Science or a related technical field. 4+ years of Python or Java development experience. 4+ years of SQL experience (No-SQL experience is a plus). 4+ years of experience with schema design and dimensional data modeling. Ability to manage and communicate data warehouse plans to internal clients. Experience designing, building, and maintaining data processing systems. Experience working with a cloud platform such as Snowflake / Azure or Databricks.
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