Responsibilities: Platform Design and Development:

• Lead the design, development, and implementation of a scalable, reliable, and efficient analytical data platform.
• Influence decisions on technology and tool selection for data ingestion, storage, transformation, and analysis for the analytics platform.
• Contribute to the overall data architecture and strategy, ensuring alignment with business needs and best practices.

Data Pipeline Engineering:

• Build and maintain robust ETL/ELT pipelines to ingest, transform, and load data from various sources into the data warehouse (e.g., cloud storage, databases, APIs).
• Develop and optimize data models for analytical use cases, ensuring data quality, consistency, and accessibility.

Data Quality and Governance:

• Establish and enforce data quality standards and processes to ensure data accuracy and integrity.
• Implement data governance policies and procedures to manage data access, security, and compliance for analytics use cases
• Proactively identify and address data quality issues, working with stakeholders to resolve root causes.

Collaboration and Communication:

• Partner with data scientists, analysts, and other engineers to understand their data needs and provide solutions.
• Effectively communicate technical concepts and designs to both technical and non-technical audiences.
• Mentor and guide data engineers, fostering a culture of learning and collaboration.

Innovation and Continuous Improvement:

• Stay up-to-date on the latest trends and technologies in data engineering and analytics.
• Identify opportunities to improve existing data processes and tools.
• Proactively propose and implement innovative solutions to address data challenges.

Required Qualifications & Skills:

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
• 5+ years of experience in data engineering, with a focus on building analytical data platforms.
• Demonstrated experience with cloud data warehousing solutions (e.g. BigQuery, Snowflake, Redshift).
• Strong proficiency in SQL and experience with data modeling techniques (e.g., star schema, dimensional modeling).
• Experience building and maintaining ETL/ELT pipelines using tools like Dagster, Apache Airflow, dbt, or similar.
• Experience with programming languages such as Python, Java, or Scala.
• Experience with data governance and data quality tools and processes is highly desirable.
• Excellent problem-solving and analytical skills, along with passion for data and a commitment to data quality.

Work-life, Culture & Perks:

• Compensation: The salary range for this role is up to 225K base with flexibility, plus a meaningful equity plan.
• Well-Being: Full medical, dental, vision, short- & long-term disability, 401k matching. 100% of the employee contribution up to 3% and 50% of the next 2%
• Home & Family: Flexible PTO, 100% paid parental leave (16 weeks for primary caregivers and 12 weeks for secondary caregivers), sick days, paid time off. For new parents returning to work we offer a flexible schedule. We also offer sleep training to help you and your family navigate life schedules with a newborn.
• Office Life: Catered lunches, happy hours, pet-friendly spaces, and home office stipend.
• Growth & Training: $1,000/year for each employee for professional development, as well as upskilling opportunities internally
• Sponsorship: We are open to sponsoring candidates currently in the U.S. who need to transfer their active H1-B visa

EvolutionIQ appreciates your interest in our company as a place of employment. EvolutionIQ is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees