Lead Data Architect

2 days ago


Atlanta, Georgia, United States Seneca Resources Full time
Lead Data Engineer

At Seneca Resources, we are seeking a highly skilled Lead Data Engineer to join our team. As a key member of our data engineering team, you will be responsible for designing and implementing data pipelines, overseeing the technical output of a team of data engineers, and ensuring optimal data delivery architecture.

Key Responsibilities:

  • Lead a team of data engineers through architecture, design, and implementation of data pipelines.
  • Mentor fellow data engineers and contribute to ongoing process improvements for the team.
  • Evaluate business needs and objectives and align architecture/designs with business requirements.
  • Build data pipelines required for the optimal extraction, transformation, integration, and loading of raw data from various sources.
  • Assemble large, complex data sets and model data in a way that meets functional and non-functional business requirements.
  • Create data tools for analytics team members to generate innovative industry insights.
  • Implement data tagging mechanisms and metadata management to accurately classify and make data visible to the organization.
  • Build processes to identify and improve data quality, consistency, and effectiveness.
  • Ensure data is managed in accordance with information privacy and protection policies.
  • Use agile software development processes to iteratively improve data management systems.
  • Identify opportunities for automation and advocate for best practices and continued learning.

Requirements:

  • Bachelor's/Tech School degree in Computer Science, MIS, or Engineering, or relevant technical field, and/or commensurate years of real-world experience in software engineering.
  • 7+ years of relevant experience in data management.
  • 5+ years in data engineering with detailed knowledge of data warehouse technical architectures, infrastructure components, ETL/ELT.
  • 3+ years of experience with Cloud-based DW such as Redshift, Snowflake, etc.
  • Technical expertise with data models, data mining, and segmentation techniques.
  • Experience in data acquisition, transformation, and storage design using design principles, patterns, and best practices.
  • Experience with performance analysis and optimization.
  • Experience with relational SQL and NoSQL databases, including Postgres and Cassandra.
  • Experience with data pipeline and workflow management tools.
  • Experience with AWS cloud services: EC2, EMR, RDS, Redshift, Modern data platforms, Snowflake, dbt, Fivetran, and Airflow.
  • Experience with stream-processing systems: Kafka, Storm, Spark-Streaming, etc. Data engineering certification is a plus.

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