Staff Engineer

The Staff Engineer will oversee the development and optimization of our data architecture, data flow, and data management processes. This role requires a combination of technical expertise and strong leadership skills to guide a team of data engineers in designing, building, and maintaining scalable data solutions. The role will ensure that data processes are reliable, secure, and aligned with business goals, enabling data-driven decision-making across the organization.

Responsibilities

• The role includes but is not limited to the following duties and responsibilities:
• Leadership
• Lead and manage a team of data engineers, fostering an environment of continuous learning and professional growth.
• Develop and implement data engineering strategies aligned with company objectives and best practices.
• Collaborate closely with data science, analytics, product, and IT teams to understand data needs and deliver solutions.
• Data Architecture & Infrastructure
• Oversee the design, implementation, and maintenance of the data infrastructure to support data processing and analytics.
• Design and optimize data pipelines for extracting, loading, and transforming data (ETL/ELT), ensuring high quality, scalability, and resilience.
• Implement data integration solutions to support multiple data sources and platforms.
• Data Governance & Quality
• Ensure data governance, security, and compliance with relevant standards (e.g., GDPR, HIPAA) across data solutions.
• Develop and enforce policies for data quality, accessibility, and performance.
• Implement monitoring and logging practices to proactively detect and address data issues.
• Innovation & Continuous Improvement
• Identify opportunities to improve data engineering processes and tools, staying current with emerging technologies.
• Develop proof-of-concept solutions to explore new ways to leverage data and automation.
• Drive initiatives to streamline data workflows, improve efficiency, and support self-service data capabilities.

Qualifications and Experience

• Bachelor’s or master’s degree in computer science, Data Engineering, Information Systems, or a related field.
• 8+ years of experience in data engineering, with at least 2 years in a management or team leadership role.
• Proficiency in data engineering tools and technologies such as SQL, Python, Apache Spark, and data warehousing solutions (e.g., Snowflake, Redshift).
• Experience with cloud platforms (e.g., AWS, Azure, GCP) and cloud-based data solutions.
• Strong understanding of ETL/ELT processes, data modeling, and data pipeline design.
• Familiarity with data governance and regulatory standards.
• Excellent problem-solving skills and the ability to work well in cross-functional teams.
• Strong communication skills, with the ability to clearly explain complex technical concepts to both technical and non-technical stakeholders.

Desired Qualifications and Experience

• Familiarity with DevOps and CI/CD practices for data engineering.
• Exposure to AWS Glue, ClickHouse, Databricks, Airflow will be a plus
• Background in implementing machine learning models in production environments is a plus.