Senior Data Analytics Engineer

WorkWave

1d • Remote

About The Position

We are seeking an innovative Senior Data Engineer to join our Startup AI and Data Analytics Business Unit. This role is a critical bridge, connecting technical engineering with business strategy. Beyond just managing tickets or building pipelines, you will take full ownership of the data ecosystem. You will play a pivotal role in supporting our AI/ML initiatives , managing the modern data stack while simultaneously answering critical business questions to ensure data accessibility, reliability, and scalability. WHAT YOU'LL DO: Ecosystem Ownership & Strategy Own the Data Ecosystem: Build and maintain robust data pipelines and ETL processes, taking full responsibility for the health, cost, and observability of the stack to prevent downtime before it impacts stakeholders. Business-First Data Modeling: Design and manage data warehouses to support advanced analytics, focusing on creating "Gold Standard" data models that make self-service easy in platforms like PowerBI, Tableau, and Sigma. Documentation & Governance: Maintain comprehensive documentation of all data engineering processes to enable stakeholder self-service, following the industry’s best practices. Engineering & Execution Infrastructure Development: Design and manage data lakes, warehouses, and databases to support advanced analytics and AI workflows. Performance Tuning: Act as a SQL/Python expert to optimize data pipelines and troubleshoot issues proactively, ensuring queries are efficient and scalable. Data Quality Management: Implement frameworks that ensure data reliability across the organization, ensuring smooth integrations across systems. Analytics Translation & Collaboration Bridge the Gap: Collaborate with cross-functional product, engineering teams, and customers to translate vague business goals into precise technical requirements. Support AI/ML: Create models that specifically enhance Analytics and AI/ML projects. WHO YOU MIGHT BE: We know that great talent comes from many backgrounds. If you are a technical expert who cares about the business "why," we want to hear from you. The Product-Minded Engineer: You are a Senior Data Engineer who is tired of just "taking tickets." You want to understand the business strategy behind the data and take ownership of the full lifecycle. The Analytics Architect: You have a background in BI or Analytics but have grown into a "Ninja-level" technical expert in SQL and Python. You build pipelines not just to move data, but to answer questions. The Startup Builder: You have worked in small teams driving innovative solutions and are comfortable wearing multiple hats—from architecting infrastructure to troubleshooting a dashboard.

Requirements

• 5+ years of experience in data engineering roles, including taking ownership of pipelines and optimizing infrastructure.
• Technical "Ninja" Skills: Ninja-level proficiency in SQL (specifically CTE optimization) and Python (complex scripting and ML/AI).
• Pipeline Architecture: Expertise in architecting data pipelines and ETL processes, with tools like Fivetran, Snowflake, and DBT.
• Business Intuition: Proven ability to apply business intuition, leveraging analytical skills to present complex data insights and actionable recommendations to technical and non-technical stakeholders.
• Visualization Proficiency: Experience building visual data analytic business-driven solutions using tools like PowerBI, Sigma, or similar analytic tools.
• Masters degree in engineering or analytics

Nice To Haves

• Cloud & Big Data: Familiarity with cloud platforms like AWS and experience with big data technologies such as Snowflake.
• Leadership: Proven experience in leading data engineering projects and integrating data from multiple sources.
• Small Team Experience: You have worked in small teams driving innovative solutions and thrive in agile environments.

Responsibilities

• Own the Data Ecosystem: Build and maintain robust data pipelines and ETL processes, taking full responsibility for the health, cost, and observability of the stack to prevent downtime before it impacts stakeholders.
• Business-First Data Modeling: Design and manage data warehouses to support advanced analytics, focusing on creating "Gold Standard" data models that make self-service easy in platforms like PowerBI, Tableau, and Sigma.
• Documentation & Governance: Maintain comprehensive documentation of all data engineering processes to enable stakeholder self-service, following the industry’s best practices.
• Infrastructure Development: Design and manage data lakes, warehouses, and databases to support advanced analytics and AI workflows.
• Performance Tuning: Act as a SQL/Python expert to optimize data pipelines and troubleshoot issues proactively, ensuring queries are efficient and scalable.
• Data Quality Management: Implement frameworks that ensure data reliability across the organization, ensuring smooth integrations across systems.
• Bridge the Gap: Collaborate with cross-functional product, engineering teams, and customers to translate vague business goals into precise technical requirements.
• Support AI/ML: Create models that specifically enhance Analytics and AI/ML projects.

Benefits

• Employees can expect a robust benefits package, including health and dental and 401k with company match
• Find your perfect work/life balance with our Flexible Time Off policy or generous PTO plan (role dependent) and paid holidays
• Up to 4 weeks paid bonding leave
• Tuition reimbursement
• Robust Employee Assistance Program through TotalCare offering free counseling 24/7/365, plus financial counseling, legal guidance, adoption assistance services and much more!
• 24/7 access to virtual medical care with Teladoc
• Quarterly awards based on peer nominations
• Regional discounts and perks
• Opportunities to participate in charitable events and give back to the community

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 501-1,000 employees