Data Warehouse Engineer

Exciting Opportunities at Maverick Payments!

Join our fast-paced, growing company and further your career with Maverick Payments, where you can thrive, your ideas are valued, and your colleagues feel more like family than coworkers!

About Payments: Maverick Payments is a family-owned and privately held full-service payment provider. Located in Calabasas, California, Maverick has created innovative technology designed for sales organizations, such as ISO’s and ISV’s, looking to monetize payments by reselling our white-labeled payments stack. Our payment products include merchant acquiring services, a proprietary gateway, ACH processing, fraud & chargeback tools, analytics, and other value-add services. Maverick’s team includes underwriting, risk management, compliance & legal, technology & product development, on-boarding, customer support, information technology, and more.

About the Position: 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 Optimize Synapse cost and performance: distribution strategies (hash/round‑robin/replicated), partitioning, indexing and statistics, workload management, scale up/down and pause/resume patterns, and archival/retention strategies. Collaborate with vendors during Phase 1; participate in code reviews, document architecture decisions (ADRs) and platform standards. Integrate Microsoft Purview for data lineage/catalog for transformation governance where appropriate. 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). Train internal stakeholders on basic SQL and data request procedures; contribute to architecture diagrams. Assist with PCI‑DSS and SOC 2 reviews (encryption at rest/in transit, RBAC/ACLs, Key Vault, Private Link, Managed Identity, least privilege). Stay current on Azure/Synapse best practices, security updates, and cost optimization. Attend vendor training in Phase 1; pursue DP‑203, DP‑300 (preferred). Share knowledge with the Director and future data science hires via code examples, patterns, and mentoring. Deliver specialized data engineering enhancements as directed by the Data Team Director. Support ad‑hoc analysis, process improvements, and cross‑functional analytics. Evaluate emerging Azure services and tooling for platform improvement. Other duties as assigned. Qualifications: 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) Advanced SQL/T‑SQL; performance tuning; query optimization; indexing; statistics; partitioning; workload management Azure Data Factory; pipeline orchestration; triggers; parameterized reusable templates; error handling; retries; idempotency Azure Synapse (dedicated/serverless SQL pools); PolyBase/COPY INTO; distribution strategies (hash/round‑robin/replicate) Azure Data Lake Gen2; Parquet/Delta; hierarchical folder structures; retention/archival; lifecycle management Incremental loads; CDC; SCD Type 2; watermarking; late‑arriving data; schema evolution Data modeling (Kimball); dimensional schemas; semantic layers; Power BI model optimization Observability & reliability: Azure Monitor, Log Analytics, KQL, alerts, dashboards; SLA/SLO adherence, post‑mortems Security & governance: RBAC/ACLs, Key Vault, Managed Identity, Private Endpoints/Virtual Networks, data masking, tokenization, Purview lineage/catalog DevOps: Git, pull requests, code reviews; CI/CD (Azure DevOps/GitHub Actions); IaC (ARM/Bicep/Terraform) Cross‑functional communication; clear documentation; vendor collaboration; prioritization by business impact; ownership mindset What We Offer: 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! Pay Range: $140K- 160K This position will consider remote work for candidates in the following states: AZ, CA (outside Los Angeles), CO, FL, GA, ID, IN, KS, KY MA, MD, ME, NE, NC, NJ, NV, NY, OH, OR, PA, TN, TX, UT, VA, WA

Maverick Payments is an Equal Opportunity Employer.

Pay Transparency Notice: At Maverick Payments, we believe in openness, honesty, and empowering our candidates to make informed career choices. As part of our commitment to transparency, we disclose the salary range for our positions. These ranges reflect our dedication to fair compensation practices and recognize the value that each team member brings to our organization. The final salary offer will be based on factors such as your experience, skills, and qualifications.

Non-Solicitation from Third Parties: Do not contact Maverick Payments about this position unless you are a job seeker and potential applicant for this position. Do not contact Maverick Payments about other services, products or commercial interests.

Notice to Agency and Search Firm Representatives: Maverick Payments is not accepting unsolicited resumes from agencies and/or search firms for this or other job postings. Resumes submitted to any Maverick Payments employee by a third-party agency and/or search firm without a valid written and signed search agreement, will become the sole property of Maverick Payments. No fee will be paid if a candidate is hired for this position as a result of an unsolicited agency or search firm referral.

Fair Chance Ordinance: Maverick will consider qualified applicants with criminal histories in a consistent manner with the Los Angeles Fair Chance Initiative for Hiring.