Mid Data Ops Analyst

At DevSavant, we are a trusted technology partner specializing in Software Development, Data Engineering, AI/Machine Learning, Cloud Solutions, Automation Testing, and UI/UX Design. We deliver innovative, high-quality solutions with a focus on excellence and results. Our people are at the heart of everything we do, fostering a culture of growth and well-being. Join us and thrive in a supportive, success-driven environment.

We're looking for a Mid Data Operations Analyst to join our client's Data Operations team to ensure predictable, accurate and timely delivery of data to internal stakeholders and our customers. In this role, you’ll become a vital link between our Commercial strategy and technical execution, translating complex customer needs into actionable data solutions. You will have the opportunity to collaborate with Data Science, Engineering, Insight Analysts, and clients directly.

Antenna, our client, is a remote-first company, and we are looking for candidates who can work during US business hours. You will report to our VP Data Operations.

• Strategic thinker with 4+ years of hands-on experience in data-focused roles.

• Expert in SQL, Excel, DBT and business intelligence tools (e.g. Looker, Redash), comfortable navigating complex ETL systems and messy data.

• Proven ability to organize, analyze and vet large volumes of data with great attention to detail.

• Strong communication and stakeholder management skills; able to translate technical concepts and align Data Ops initiatives with customer-centric objectives.

• Passionate about solving customer problems.

• Self-starter with the ability to carry multiple initiatives, prioritize time and resources, and meet deadlines in a fast-moving environment.

• Bonus: Experience using automation tools and AI-driven solutions to streamline data workflows and elevate data product reliability.

• Investigate anomalous data to make a judgment call on whether trends represent data quality errors or real-world events.

• Act as the first responder for data issues and inquiries. Educate commercial stakeholders about data definitions and nuances.

• Manage updates to QA tests and dashboards to streamline ongoing QA checks.

• Investigate data restatements and data science models. Coordinate data fixes in partnership with Engineering and Data Science teams (internally) and data vendors (externally).

• Perform data quality investigations to understand why Antenna data does not align to customer’s first party data. Present findings to customers directly.

• Run new coverage feasibility, and propose solutions to update methodology and pipeline capabilities.

• Coordinate monthly data releases in Looker, and weekly data releases via ad hoc reports.

Required skills

• Technical:

  • 4-6 years of hands-on experience in data-focused roles

  • Proficient in performing advanced SQL queries for research and reporting, ensuring data quality and integrity.

  • Track record of analyzing large datasets, mining for inconsistencies and recognizing patterns.

  • Capable of rectifying data inconsistencies and developing scalable data quality test plans to uphold high standards of data quality.

  • Proficient in managing product lifecycles and communicating action plans and timelines to clients.

  • Experience collaborating with Engineering and Data Science teams.

  General:

  • Ability to think strategically and translate client requirements, data feasibility assessments and limitations, and product vision into actionable strategies.

  • Collaborate strategically with product and commercial teams to transform raw data into actionable product features and improvements, directly impacting customer satisfaction.

  • Strong communication skills with experience in managing stakeholders and effectively communicating Data Ops initiatives to drive organizational objectives.

  • Proficient decision-making skills, adept at prioritizing tasks and project managing cross-functional teams.

  • Efficient management of data processes and documentation.

  • Nice to have:

    • Prior experience in managing data vendors, including selection, negotiation, and issue resolution.

    • Ability to mentor and supervise team members, ensuring adherence to best practices in data operations.