Senior Data Engineer - Reorg

We are seeking a highly skilled and experienced Senior Data Engineer with a strong background in building and managing data pipelines, data warehouses, and data lakes. As a Senior Data Engineer, you will play a pivotal role in our organization's data infrastructure, enabling efficient and reliable data processing, storage, and analysis.

Responsibilities:

• Design and develop robust, scalable, and efficient data pipelines to support the extraction,
  transformation, and loading (ETL) processes from various data sources into data warehouses
  and data lakes.
• Collaborate closely with cross-functional teams, including data scientists, analysts, and software
  engineers, to understand data requirements and design optimal solutions.
• Build and manage data warehouses and data lakes to store and organize large volumes of
  structured and unstructured data efficiently.
• Implement data governance processes and best practices to ensure data quality, integrity, and
  security throughout the data lifecycle.
• Identify and address performance bottlenecks, data inconsistencies, and data quality issues in
  data pipelines, warehouses, and lakes.
• Develop and maintain monitoring and alerting systems to proactively identify and resolve data-related issues.
• Continuously evaluate and explore emerging technologies and tools in the data engineering space to improve data processing efficiency and scalability.
• Mentor and guide junior data engineers, providing technical leadership and fostering a collaborative and innovative environment.

Requirements:

• Bachelor's degree in Computer Science or a related field.
• Proven experience (minimum 5 years) in building and managing data pipelines, data warehouses, and data lakes in a production environment.
• Proficiency in programming languages such as Python, SQL and experience with data processing frameworks like Apache Spark or Apache Beam.
• Experience ETL/ELT frameworks and tools like AWS Glue, dbt, Airflow, Airbyte, etc.
• In-depth knowledge of relational databases (e.g., MySQL, PostgreSQL) and experience with columnar storage technologies (e.g., Redshift, Snowflake).
• Strong understanding of distributed systems, data modeling, and database design principles.
• Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and experience in deploying data infrastructure on the cloud.