Sr. Data Engineer / Scientist - Data Quality & Insights Team

Internally, the team supports Customer Success, Sales, Marketing, Product, and the executive team. Understanding the question behind a request, choosing the analysis that actually answers it, and explaining the result to a non-technical audience matter as much as the modeling itself.

The role also owns the delivery of technical projects such as store merges and large data migrations, mentors engineers on the team, and sets the standard for how analysis moves from a notebook to a production deliverable., * Build, validate, and deploy machine learning models in Databricks (PySpark, Spark SQL, Delta Lake, MLflow) for forecasting, scoring, segmentation, and anomaly detection

• Run statistical analyses, including correlation, regression, hypothesis testing, cohort analysis, and time-series analysis, and state plainly what the data does and does not support
• Architect data quality frameworks in Databricks using profiling, rule-based validation, and statistical anomaly detection, and define how they move from notebooks to production jobs
• Build the pipelines and feature sets that analytics and ML workloads depend on
• Design advanced Power BI models and reports that make findings usable by people who will never open a notebook

Business partnership

• Serve as the analytical partner to Customer Success, Sales, Marketing, Product, and the executive team: understand the question behind the request, scope the analysis, and deliver a clear answer
• Present findings to technical and non-technical audiences, including executive readouts
• Turn recurring requests into self-service reporting so the team spends its time on new questions
• Build the capacity to work directly with customers on custom data projects as that need develops

Data platform and quality

• Lead complex store merges and architect store migration strategies
• Own and drive resolution of complex data migration issues
• Design and oversee supplemental data import processes including opt-outs, customer lists, and service data at scale
• Own and drive resolution of complex non-import related Data Investigations and Data Mods
• Develop and maintain custom frameworks for data ingestion and transformation
• Lead troubleshooting of critical production issues and incident response efforts

Leadership and delivery

• Own technical projects from inception to completion: timelines, milestones, resource allocation, and cross-functional coordination; target audiences may include internal technical teams, internal business teams, customers, and partners
• Mentor team members across skill levels, including upskilling AI-first data engineers on Databricks, PySpark, and applied statistics
• Lead by example by establishing and following best practices for analysis and pipeline code
• Serve as technical liaison with other departments

• 3+ years applying statistics and machine learning to business problems: regression, classification, clustering, time-series forecasting, correlation and causal analysis, hypothesis testing, and anomaly detection, with the judgment to know when each method misleads
• Hands-on experience building and deploying ML and analytics workloads in Databricks or a comparable lakehouse platform (PySpark, Spark SQL, Delta Lake, Jobs/Workflows); this is required, not preferred
• Strong Python for data science (pandas, scikit-learn, statsmodels, or equivalent) alongside SQL
• 5+ years working with SQL and database development, including 3+ years with T-SQL and Microsoft SQL Server
• Advanced Power BI development and architecture experience, and the judgment to choose the visualization that answers the question
• Track record of partnering with business teams such as Customer Success, Sales, Marketing, Product, or executive stakeholders to define the question, deliver the analysis, and drive a decision
• Excellent written and verbal communication, including explaining statistical results and their limits to non-technical audiences
• Strong understanding of ETL/ELT architectures at scale, including lakehouse patterns
• Strong scripting and automation framework development skills
• Experience managing complex production deployments
• Comfort with after-hours work and leading on-call efforts
• Drives innovation and process enhancement
• Ensures project outcomes drive customer success
• Builds bridges across teams and departments
• Leads through challenges and setbacks
• Delivers projects on time and on quality, * Experience with CRM systems and automotive dealership data, or knowledge of multiple CRM providers
• Advanced Databricks experience: Unity Catalog governance, Delta Lake optimization, and MLflow model registry
• MLOps and feature store implementation
• Experiment design (A/B testing, uplift measurement) and causal inference methods
• Experience presenting to or working directly with external customers on data projects
• Experience with PostgreSQL or other database platforms
• Knowledge of AWS services (EC2, RDS, S3, CloudWatch)
• Knowledge of C# or other scripting languages
• Experience with modern data stack technologies (Snowflake, dbt)
• Understanding of data governance and compliance requirements
• Performance tuning at enterprise scale
• Streaming technologies (Kafka, Spark Streaming)
• Project management certifications (PMP, Agile, Scrum)

Pluses:

• Experience with Twilio or other CPaaS.
• Experience with Kafka.
• Experience with Amazon Web Services (e.g. S3, EC2, EKS, etc.)
• Experience writing APIs to be consumed by 3rd parties.
• Experience with speech-to-text, or building product features on top of LLM or ML output.
• Familiarity with telecom regulatory requirements (A2P/10DLC, TCPA, STIR/SHAKEN, call recording consent).

• Competitive salary + bonus + annual merit increases
• Health, vision, and dental insurance (eligible on day 1)
• 401K with matching up to 4% (eligible after 90 days)
• 9 company holidays + 15 FTO days in first year
• Pluralsight subscription
• Professional growth opportunities
• Short/Long-Term Disability Insurance
• Employer-paid Life Insurance
• Additional Voluntary Life Insurance
• Accident Insurance
• Critical Care Insurance
• Hospital Indemnity Insurance
• Employee Assistance Program