Senior Data Engineer

Job Responsibilities

• Lead the design, development, and implementation of complex data pipelines using various ETL/ELT tools and programming languages (e.g., Python, Scala, SQL).
• Develop and optimize data models, schemas, and data warehousing solutions (e.g., Databricks, AWS Redshift) to ensure high performance and data integrity.
• Serve as a recognized authority across multiple data technologies and business domains, independently resolving ambiguous or complex data problems.
• Collaborate with data scientists, analysts, and other collaborators to understand data requirements and translate them into technical solutions.
• Implement and maintain data quality checks, data governance policies, and data security measures.
• Troubleshoot and resolve data pipeline, infrastructure, and platform issues, ensuring data availability and reliability.
• Evaluate and recommend new data technologies and tools to improve efficiency and capabilities.
• Challenge existing approaches and recommend improvements to team and business data processes that drive innovation.
• Mentor and coach data engineers by sharing knowledge in specialized technologies and business domains to increase team technical growth.
• Promote ideas and influence technical decisions across multiple teams, including business and non-engineering collaborators.
• Participate in code reviews and ensure adherence to coding standards and architectural guidelines.
• Document data flows, processes, and system architectures comprehensively.

Qualifications

• Bachelor's degree in computer science, Engineering, Information Systems, or a related quantitative field.
• 8+ years of experience in data engineering, data warehousing, or a related field.
• Proven expertise in designing and building scalable data pipelines using cloud-based platforms (e.g., AWS, Azure, GCP).
• Strong hands-on experience with Databricks (e.g., Delta Lake, notebooks, workflows, Unity Catalog) for building and optimizing large-scale data solutions.
• Hands-on experience with Apache Airflow for orchestrating, scheduling, and monitoring complex data pipelines.
• Strong proficiency in SQL and at least one programming language (Python, Scala, Java).
• Extensive experience with data warehousing concepts and technologies (e.g., Airflow, Databricks, Redshift, Teradata).
• Experience with data visualization tools (e.g., Tableau, Power BI, Looker) to support analytics, reporting, and stakeholder communication.
• Solid understanding of data modeling techniques (dimensional, relational, star/snowflake schemas).