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.
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Last updated on Dec 13, 2024