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 tools like Apache Spark, Kinesis, and AWS services. Evaluate and recommend emerging technologies to ensure our data platform remains cutting-edge. This role requires extensive experience in data engineering and strong programming skills.

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