Staff Data Engineer

Summary

Join our team as a Staff Data Engineer and lead the design, development, and optimization of our data architecture, pipelines, and workflows. You will serve as a technical lead, setting best practices, mentoring team members, and solving complex data challenges. Collaborate with cross-functional teams to design systems that transform raw data into actionable insights. Build and maintain batch and real-time data pipelines using various tools. Ensure data quality, governance, and security. Evaluate and recommend emerging technologies to keep our data platform innovative and scalable. We offer competitive compensation and benefits, and the opportunity to expand your skills and help reshape the future of work.

Requirements

• 12+ years of experience in data engineering field, with at least 2 years in a senior or staff-level role
• Expertise in designing and implementing scalable data architectures for big data platforms
• Strong programming skills in Python, Scala
• Deep experience with distributed data processing systems such as Apache Spark, Databricks, Delta Lake
• Proficiency with relational databases (e.g., PostgreSQL, MySQL) and NoSQL databases (Dynamo)
• Strong understanding of ETL/ELT workflows, data warehousing concepts, and modern data lake architectures
• Employ the established Data Governance model to sustain Data Quality for the data objects and implement the necessary operating mechanisms to ensure compliance
• Knowledge of CI/CD practices
• Excellent problem-solving skills and the ability to design creative, efficient solutions for complex data challenges
• Proactive, self-driven, and detail-oriented with a strong sense of ownership

Responsibilities

• Design, and implement scalable and reliable data pipelines, ensuring the processing of large volumes of structured and unstructured data
• Define and enforce data engineering best practices, coding standards, and architectural principles across teams
• Conduct code reviews and provide mentorship to junior and senior data engineers
• Build and maintain batch and real-time data pipelines using tools such as Apache Spark, Kinesis, and AWS services
• Works with multiple teams to coordinate the event-driven architecture, managing inter-dependencies and promoting consistency
• Ensure data quality, governance, and security by implementing monitoring, validation, and compliance tools
• Partner with product, analytics, and data science teams to understand business requirements and translate them into technical solutions
• Work closely with DevOps and software engineering teams to deploy and maintain production-ready data infrastructure
• Evaluate and recommend emerging technologies and frameworks to ensure the data platform remains future-proof
• Drive initiatives to improve the performance, scalability, and efficiency of existing systems

Preferred Qualifications

Background in AI, machine learning pipelines is a plus

Benefits

Competitive compensation and benefits