Data Warehouse Engineer

🔥 13 hours ago

🌵 Arizona, California, +21 more states – Remote

🌵 Arizona – Remote 🏄 California – Remote ⛰️ Colorado – Remote 🐊 Florida – Remote 🥔 Idaho – Remote 🌪️ Kansas – Remote 🐎 Kentucky – Remote 🦞 Maine – Remote 🌾 Nebraska – Remote 🎰 Nevada – Remote 🏖️ New Jersey – Remote 🗽 New York – Remote 🌲 North Carolina – Remote 🏈 Ohio – Remote 🌲 Oregon – Remote 🦀 Maryland – Remote 🍂 Massachusetts – Remote 🔔 Pennsylvania – Remote 🎸 Tennessee – Remote 🤠 Texas – Remote ⛷️ Utah – Remote ⚔️ Virginia – Remote ☕ Washington – Remote

💵 $110k - $125k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

🚰 Data Engineer

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Maverick Payments

WebsiteLinkedInAll Job Openings

51 - 200 employees

💳 Fintech

💸 Finance

☁️ SaaS

Fintech • Finance • SaaS

Maverick Payments is a full-service payment processor offering technology-driven payment solutions. Specializing in both online and in-person payment processing, Maverick Payments features advanced tools such as a comprehensive dashboard, fraud prevention capabilities, analytics, and reporting. The company provides white-labeled payment solutions and enables businesses to process transactions through their API, virtual terminal, and other integrated services. With a focus on emerging markets and offering advanced features like ACH and card-not-present transactions, Maverick Payments aids businesses of all sizes in managing chargebacks, expanding their reach, and optimizing payment acceptance and management. The company operates as a division of Maverick BankCard, Inc. and partners with several banks for streamlined operations.

📋 Description

• The Data Warehouse Engineer is a hands-on role responsible for 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. • 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.

🎯 Requirements

• 3+ years in data engineering/data warehousing or 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

• 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!