Data Warehouse Engineer

Maverick Payments

Data Warehouse Engineer responsible for end-to-end design and operation of Azure data platform at Maverick Payments. Collaborating with cross-functional teams and supporting BI analytics needs with reliable data access.

Posted 7/31/2026full-timeRemote • California • 🇺🇸 United StatesMid-LevelSenior💰 $140,000 - $160,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and operating Azure data platforms, with a strong focus on ETL/ELT processes, data quality, and performance optimization. Proficient in advanced SQL/T-SQL and data modeling techniques to support analytics and BI initiatives.

Highest-signal resume keywords

Advanced SQL/T-SQLAzure Data FactoryETL/ELT DeliveryData ModelingTroubleshooting and RCA

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

SQLT-SQLData EngineeringData WarehousingETLELTData ModelingPerformance TuningRoot-Cause AnalysisData Quality

Soft Skills

CollaborationProblem-SolvingCommunication

Tools & Technologies

Azure SynapseAzure Data Lake Gen2Azure MonitorPower BIGitAzure DevOps

Industry Keywords

Data PipelineData IntegrationSLA ComplianceData GovernanceAPI Ingestion

Tech Stack

Tools & technologies

Amazon RedshiftAzureBigQueryETLITSMSQLTerraformVault

About the role

Key responsibilities & impact

The Data Warehouse Engineer is a hands-on role responsible for the end-to-end process of designing, building, and operating Maverick’s Azure data platform.
Reporting to the Data Team Director, you will partner with external implementation resources in Phase 1 and then own daily operations, reliability, and continuous improvement of the platform.
The role balances operational excellence (pipeline uptime, SLAs, observability) with platform development (new data pipelines, sponsor bank integrations, performance/cost optimization).
Your work enables the Maverick organization to access reliable, timely, and governed data for analytics, BI, and regulatory reporting.
Monitor health and SLAs via Azure Monitor/Log Analytics, Synapse and Data Factory dashboards; respond to critical pipeline incidents within 2 hours.
Triage and resolve data integration failures (sponsor bank files, CRM/ITSM connectors, API ingestions), distinguishing data quality vs. pipeline vs. infrastructure issues; escalate when needed.
Perform root-cause analysis (RCA) and drive corrective actions; maintain and conduct post-mortems.
Support users with ad‑hoc SQL, Power BI connectivity, refresh scheduling, and semantic model best practices.
Track pipeline performance and data freshness, optimize query runtimes, memory, and SLA compliance.
Design and build Azure Data Factory pipelines (ETL/ELT) for batch and incremental ingestion using parameterized, reusable templates.
Write and optimize T‑SQL in Synapse SQL pools for reliability and maintainability.
Implement incremental loads, CDC (Change Data Capture), idempotent retries, and robust error handling.
Onboard new sponsor banks and data sources against the Director’s roadmap; standardize patterns for file-based (CSV/JSON/Parquet/Delta) and API-based data.
Strengthen data quality and observability with validation checks, reconciliations, and anomaly detection.
Collaborate with vendors during Phase 1; participate in code reviews, document architecture decisions (ADRs) and platform standards.
Create and maintain runbooks (“respond to X failure”), troubleshooting guides, and common query patterns.
Document pipeline architecture, data lineage, schemas, and transformation logic for knowledge transfer.
Maintain a data dictionary/metadata (descriptions, refresh cadence, PII tags, sensitivity labels).

Requirements

What you’ll need

5-8 years in Data Engineering/Data Warehousing or closely related technical roles.
Advanced SQL/T-SQL: complex queries, stored procedures, views, indexing, and performance tuning.
Hands-on Azure: Data Factory, Synapse SQL, Data Lake Gen2, Key Vault (or strong equivalents: Snowflake, BigQuery, Redshift).
Proven delivery of ETL/ELT for file-based (CSV/JSON/Parquet) and API data sources.
Strong data modeling: star/snowflake, dimensional modeling, fact/dimension tables, SCDs (Type 1/2).
Git proficiency and CI/CD concepts for infra/pipeline deployment (Azure DevOps/GitHub Actions; ARM/Bicep/Terraform a plus).
Demonstrated troubleshooting and RCA across complex systems; able to drive solutions independently.
Experience supporting BI/analytics consumers (Power BI preferred; semantic models, incremental refresh, gateway basics).

Benefits

Comp & perks

Competitive Salary, Bonuses and Incentives.
Comprehensive employer sponsored health, vision, and dental insurance programs.
Paid time off, Paid Sick and Paid Holidays.
401K plan with up to a 3% matching contribution.
Commitment to Career Development and Advancement.
Vibrant Office Culture, Team Building, Birthdays, Work Anniversaries, Snacks, and more!