Senior Data Analytics Engineer

Company Description:BETSOL is a cloud-first digital transformation and data management company offering products and IT services to enterprises in over 40 countries. BETSOL team holds several engineering patents, is recognized with industry awards, and BETSOL maintains a net promoter score that is 2x the industry average.BETSOL’s open source backup and recovery product line, Zmanda (Zmanda.com), delivers up to 50% savings in total cost of ownership (TCO) and best-in-class performance.BETSOL Global IT Services (BETSOL.com) builds and supports end-to-end enterprise solutions, reducing time-to-market for its customers.BETSOL offices are set against the vibrant backdrops of Broomfield, Colorado and Bangalore, India.We take pride in being an employee-centric organization, offering comprehensive health insurance, competitive salaries, 401K, volunteer programs, and scholarship opportunities. Office amenities include a fitness center, cafe, and recreational facilities.Learn more at betsol.comJob Description:The Senior Data Analytics Engineer will lead the design, development, and evolution of our enterprise analytics platform. This role blends hands on technical ownership with team leadership, offering the opportunity to shape both our data architecture and our analytics engineering practice.You will own critical components of our Data Vault 2.0 warehouse on Snowflake, mentor a growing team of Analytics Engineers, and serve as the connective layer between raw operational data and business critical insights.Our data environment goes well beyond a typical dbt project. We operate a mature, multi tenant analytics warehouse integrating 13+ source systems (including Five9, inContact, Serenova, Salesforce, Shiftboard, and NetSuite) across 15+ client engagements. You’ll work across the full analytics stack—from staging and raw vault to business vault, prime stage, and client specific information marts—delivering clean, tested, and well documented models that support finance, operations, and compliance reportingQualifications:Required QualificationsBachelor’s degree in a quantitative or technical field, or equivalent professional experience5+ years of production SQL experience, including:Window functionsCTEsPerformance tuningScalable modeling patternsStrong Snowflake expertise, including:Warehouse sizing and query profilingRole‑Based Access Control (RBAC)Cost monitoringIncremental and MERGE strategiesHands‑on experience with dbt, including:Modular model designref and source usageGeneric and custom testsYAML schema configurationCI workflows on pull requestsSolid understanding of Data Vault 2.0 or similar methodologies (e.g., Kimball, Anchor Modeling)Proficiency with Git and GitHub workflows (branching, PRs, code reviews)Proven ability to lead or mentor junior and mid‑level engineersPreferred QualificationsExperience building Streamlit or other Python‑based data applicationsFamiliarity with contact center platforms (Five9, inContact, Serenova, or similar)Experience using dbt Cloud for orchestration and environment managementExposure to data integration tools such as Fivetran or AirbyteComfort working with semi‑structured data (VARIANT columns, LATERAL FLATTEN)Additional Information:What You’ll DoData Architecture & DevelopmentDesign and maintain scalable data models using dbt and Data Vault 2.0 methodologiesBuild hubs, links, and satellites (SCD Type 2), along with business vault–derived objectsDevelop performant info mart views for internal and external stakeholdersLeadership & MentorshipLead and mentor Analytics Engineers through code reviews and pair programmingEstablish and enforce standards for SQL style, testing, and documentationRaise the overall quality and consistency of analytics engineering deliverablesPerformance & OptimizationOptimize Snowflake workloads through incremental strategies, dynamic tables, and warehouse sizingApply cost‑conscious query design and performance tuning best practicesIntegration & EnablementOnboard new data sources and clients with repeatable ingestion and staging patternsFlatten and model complex semi‑structured (JSON) data effectivelyCollaboration & DeliveryPartner with Finance, Operations, Compliance, and Client Services to translate business questions into reliable data modelsParticipate in a 4‑week agile cadence with CI on pull requests and automated dbt Cloud deployments

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