
5001 - 10000 employees
Founded 2002
💸 Finance
🏠 Real Estate
Finance • Real Estate
AmeriSave Mortgage Corporation is a leading online mortgage lender offering a variety of home financing solutions, including first and second mortgages, home equity loans, and refinancing options. With 20 years of mortgage experience, AmeriSave has served over 733,603 borrowers across 49 states in the U. S. The company prides itself on providing easy and fast mortgage processes with access to quick quotes and approvals, low rates, and secure rate locks. AmeriSave is committed to helping its clients achieve financial freedom and better financial positions through responsible home equity usage and effective mortgage solutions. The company is well-regarded for its excellent customer service and accessibility, offering support in multiple languages and emphasizing easy online interactions for customer convenience.
🕒 July 7
⛰️ Colorado – Remote
💵 $100k - $170k / year
⏰ Full Time
🟠 Senior
🚰 Data Engineer
🦅 H1B Visa Sponsor
👻 Ghost score 5%
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5001 - 10000 employees
Founded 2002
💸 Finance
🏠 Real Estate
Finance • Real Estate
AmeriSave Mortgage Corporation is a leading online mortgage lender offering a variety of home financing solutions, including first and second mortgages, home equity loans, and refinancing options. With 20 years of mortgage experience, AmeriSave has served over 733,603 borrowers across 49 states in the U. S. The company prides itself on providing easy and fast mortgage processes with access to quick quotes and approvals, low rates, and secure rate locks. AmeriSave is committed to helping its clients achieve financial freedom and better financial positions through responsible home equity usage and effective mortgage solutions. The company is well-regarded for its excellent customer service and accessibility, offering support in multiple languages and emphasizing easy online interactions for customer convenience.
• Design, develop, and maintain robust enterprise data warehouse solutions that support data science, artificial intelligence, and business intelligence requirements. • Architect scalable ETL/ELT pipelines to efficiently transform raw data into structured, analytics-ready formats. • Build and manage API integrations, including hands-on API development. • Utilize T-SQL and Azure Data Factory to create, optimize, and manage data integration workflows. • Use Microsoft Fabric notebooks for transformation and orchestration where appropriate, leveraging Lakehouse and Warehouse for supplemental storage. • Ensure high data quality, integrity, and performance through meticulous query tuning and process optimization. • Collaborate with data scientists, software developers, business intelligence teams, and stakeholders to develop and deploy data solutions that meet business needs. • Translate business requirements into technical solutions and coordinate smoothly between engineering and other teams. • Lead the creation of scalable, reliable data models and optimize them for performance and usability. • Drive continuous improvement in data engineering processes and practices to keep them efficient and aligned with industry best practices. • Monitor system performance and proactively implement improvements to maximize efficiency and scalability. • Troubleshoot and resolve data-related issues to ensure reliable data delivery.
• 5+ years of hands-on experience in data warehousing, data engineering, or a similar role. • Extensive experience with T-SQL, including advanced query development and performance tuning. • 5+ years as a SQL Server / Azure SQL DBA — performance tuning, index and statistics management, execution-plan analysis, and proactive capacity planning. • Proficiency with pipeline development and configuration using Azure Data Factory (ADF). • Working familiarity with Microsoft Fabric (notebooks and pipelines for transformation, Lakehouse, and Warehouse) • Expertise in Python for data engineering tasks, including data manipulation and workflow management. • Strong understanding of data modeling, data architecture, and best practices in data governance. • Experience handling sensitive/PII data and supporting data quality and governance in a regulated, financial-services environment. • Experience preparing clean, analytics- and ML-ready datasets to support data science and AI workloads. • Excellent problem-solving skills and the ability to work independently as well as collaboratively. • Strong communication skills to effectively liaise with both technical teams and non-technical stakeholders.
• 401(k) • Dental insurance • Disability insurance • Employee discounts • Health insurance • Life insurance • Paid time off • 12 paid holidays per year • Paid training • Referral program • Vision insurance • Bonus • Referral bonuses
Apply Now🕒 July 7
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