Senior Data Engineer

<h3>📋 Description</h3> • Spark is seeking a Senior Data Engineer to join our data team. • You can be a key part of the change by helping Spark build robust data infrastructure that powers our platforms and insights. • In this role, you will be responsible for architecting, implementing, and maintaining the core data infrastructure that enables our business operations and analytics capabilities. • As a Senior Data Engineer, you'll focus on building scalable backend systems, implementing modern data tools, and improving the data pipelines that serve as the foundation of our data ecosystem. • You'll work closely with product, engineering, and the broader data team to ensure our data infrastructure meets both current needs and future growth. • Build and maintain critical data infrastructure components including (but not limited to) SFTP servers, cloud-based data warehouses, transformation and orchestration tools, and data visualization tools. • Establish monitoring, alerting, and logging systems to ensure data pipeline reliability and performance. • Develop and enforce data governance policies, including data quality checks and access controls. • Build and maintain data pipelines in dbt with analytics engineers. • Collaborate with analysts and analytics engineers to understand their data requirements and build appropriate backend solutions. • Mentor and upskill junior engineers, fostering a collaborative and growth-oriented environment. • Design, implement, and optimize scalable data pipelines using modern ETL/ELT frameworks (Airflow, GCP tools). <h3>🎯 Requirements</h3> • 5+ years of experience in data engineering roles with focus on infrastructure and backend systems • Strong Python programming skills for building data processing applications and automation • Experience designing, implementing, and troubleshooting workflows using orchestration tools like Airflow or Prefect, including custom operators and scheduling optimization • Advanced proficiency in SQL and experience implementing dbt/Dataform in production environments • Proven experience designing and implementing cloud-based data infrastructure on GCP/AWS • Experience setting up secure data transfer protocols (SFTP, API integrations) • Strong understanding of version control, CI/CD pipelines, and infrastructure-as-code principles • Excellent problem-solving skills and ability to debug complex data pipeline issues • Strong communication skills for cross-functional collaboration and technical documentation <h3>🏖️ Benefits</h3> • Equity compensation • Health care, including dental and vision through our PEO Sequoia • Flexible work location; co-working available • 401k • Paid Time Off • Monthly Remote Work Stipend (help cover costs of home-office needs) • Paid Parental Leave • Up to 12 weeks for birthing parents • Up to 8 weeks for non-birth parents • 11 paid holidays • 2 week sabbatical at 5 years of employment • Wellbeing Perks through SpringHealth, OneMedical, PerkSpot, and SoFi