Data Analytics Engineer

About the role

In this role, you will play a crucial part in ensuring that our core data products are both accurate and delivered on time. You will collaborate closely with various teams, including commercial, data science, and engineering, to make informed decisions that significantly impact client trust and overall business performance. This position is designed to be remote, with a requirement to work during U.S. business hours to align with our operational needs. You will own the integrity of the data pipeline from ingestion to presentation, identifying discrepancies before they affect downstream reporting. Your analysis will directly influence strategic choices that determine how clients perceive the reliability of our platform. You will act as a bridge between technical execution and business requirements, translating complex data findings into actionable insights. This role demands ownership of end-to-end data quality and the autonomy to drive improvements without constant supervision. You will be instrumental in fostering a data-driven culture where decisions are grounded in verified information rather than intuition.

Key facts

What you'll do

Investigate anomalies in core data products by tracing data lineage through SQL queries and dbt transformations to pinpoint root causes of inconsistencies.

Construct and maintain robust ETL processes using dbt, ensuring that data transformations are scalable, documented, and adhere to best practices for reproducibility.

Develop and implement validation frameworks that automatically check data quality across datasets, reducing manual oversight and increasing confidence in results.

Collaborate with commercial teams to interpret contract terms and translate them into data rules that ensure billing and performance metrics align precisely with agreements.

Work with data science initiatives to prepare feature datasets and provide feedback on data feasibility, helping to steer model development toward technically viable solutions.

Design and optimize SQL queries against large transactional datasets to support real-time dashboard performance and reduce latency in reporting cycles.

Partner with engineering teams to define data models in warehouse systems, ensuring that schema designs support efficient querying and long-term maintainability.

Leverage business intelligence tools like Looker or Redash to build clear, self-service dashboards that enable stakeholders to explore data without relying on constant requests.

Monitor data pipelines for failures or delays, setting up alerts and runbooks to ensure timely responses to issues that could impact client trust.

Translate ambiguous business questions into structured analytical plans, guiding stakeholders through data exploration to arrive at well-supported conclusions.

Conduct regular data audits to verify accuracy across sources, documenting findings and recommending corrective actions to prevent recurrence.

Educate non-technical stakeholders on data concepts and limitations, fostering better communication and more realistic expectations around what data can reveal.

Champion data governance practices by enforcing naming conventions, access controls, and metadata standards that keep documentation clear and searchable.

Support continuous improvement by iterating on existing dashboards and reports based on stakeholder feedback, focusing on usability and clarity over speed.

Requirements

You must possess a minimum of 7 years of hands-on experience in data-centric roles, demonstrating consistent delivery of reliable analytics in production environments.

You must be proficient in SQL, using advanced techniques such as window functions, CTEs, and joins to manipulate and analyze complex datasets effectively.

You must have expert-level skills in Excel, including the ability to clean, transform, and analyze data using formulas, pivot tables, and macros when necessary.

You must be highly skilled in dbt, building modular transformation pipelines that are easy to maintain, test, and extend over time.

You must be comfortable working with business intelligence tools such as Looker or Redash, creating and refining visualizations that communicate insights clearly to diverse audiences.

You must have proven experience organizing, analyzing, and validating large datasets, showing meticulous attention to detail and a low tolerance for inaccuracies.

You must demonstrate excellent communication skills, articulating technical concepts in plain language to stakeholders with varying levels of technical expertise.

You must show a strong commitment to resolving customer issues, using data to support decisions that enhance client satisfaction and retention.

Nice to have

Familiarity with automation tools that can streamline repetitive data tasks and reduce the risk of manual errors in routine processes.

Experience with AI-driven solutions that enhance data workflows, such as intelligent parsing or anomaly detection in large datasets.

Background in data visualization techniques that go beyond basic charting, including storytelling methods that highlight key trends and outliers.

Knowledge of data governance and compliance standards relevant to handling sensitive client information, ensuring that data practices meet regulatory expectations.

Experience working with cloud data platforms commonly used in modern analytics stacks, including warehouses where dbt and SQL are primary tools.

Practical notes

This position is fully remote; however, candidates must be available to work during U.S. business hours, preferably within U.S. time zones (Eastern, Central, Mountain, or Pacific).

You will report directly to the VP of Data Operations, ensuring that you have the support and guidance needed to excel in your role.

In summary, as a , you will be at the forefront of our data operations, driving initiatives that enhance data quality and client satisfaction. Your expertise will be pivotal in shaping our data products and ensuring their reliability, ultimately contributing to the success of our clients and the organization as a whole. If you are passionate about data and eager to make a significant impact in a dynamic environment, we encourage you to apply.