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:LeadershipLead 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 & InfrastructureOversee 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 & QualityEnsure 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 ImprovementIdentify 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.
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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 plusBackground in implementing machine learning models in production environments is a plus.