Senior Data Analyst

About the Company: Endpoint is a digital title and settlement company built from the ground up to make home closing easy for all. For many, buying or selling a home is one of life’s biggest transactions. At Endpoint, we help our customers close every deal so they can start their next chapter with confidence. Whether it’s a first-time homebuyer choosing a place to start a family, a real estate agent securing a record-breaking deal, or a proptech company scaling its services, we believe that closing on a home is a milestone worth celebrating and a process that should be easy for all parties involved.
Founded in 2018 by a diverse group of tech and real estate veterans, Endpoint develops technology that streamlines home closing for real estate agents, buyers and sellers, and empowers proptech companies and investors looking to scale their closing operations. Backed by First American Financial Corporation, a Fortune 500 company, Endpoint has secured $220 million in funding and has operations across the US.
About the Job:At Endpoint, data drives our strategic decisions, with our Data Engineering and Platform team playing a crucial role in this process. As we experience rapid growth, having accessible and actionable information is essential. We are looking for a Senior Data Analyst to join our dynamic team. In this role, you will collaborate closely with Product, Operations, Engineering, Revenue, and Business Development teams to build and maintain data solutions that provide valuable insights and support business recommendations. You will leverage your technical and analytical skills to manage stakeholder expectations and drive consensus. Additionally, you’ll play a key role in shaping the data infrastructure roadmap, ensuring that data governance and alignment are maintained across the company.

As a Senior Data Analyst, you will use your skills to

• Create, build, and manage highly scalable and efficient data pipelines for processing and integrating data from various internal and external sources.
• Design and maintain data infrastructure to support high-volume data processing, ensuring reliability, scalability, and performance to contribute significantly to the company's success.
• Collaborate closely with cross-functional teams, including Data Science, Product, and Engineering, to understand their data requirements and deliver robust solutions, emphasizing the need for solid communication and collaboration skills.
• Conduct data profiling, cleansing, and transformation to ensure data accuracy, integrity, and availability across systems.
• Identify opportunities to automate data processes and optimize existing pipelines to improve performance and reduce costs.
• Develop and maintain detailed documentation for data pipelines, data models, and workflows, ensuring alignment with industry best practices and company standards.
• Contribute to developing internal tools and frameworks that enhance data accessibility and usability across the organization.
• Support data governance initiatives by ensuring compliance with data quality standards and contributing to data stewardship efforts to maintain the integrity and reliability of our data.
• Stay abreast of the latest technologies and industry trends, continuously improve data engineering practices within the team, and cultivate a culture of continuous learning and growth.
• Develop and implement optimized data models for data warehouses and data marts to meet the needs of analytics and reporting teams.
• Drive operational excellence through a metrics-driven approach.

You will come to the Endpoint with

• 5+ years of Python expertise: Specializing in data engineering tasks like building, optimizing, and automating data pipelines. Proficiency in essential Python libraries and frameworks for data processing.
• Code quality & efficiency: Focus on writing clean, maintainable, and efficient Python code with strong practices in error handling, logging, and performance optimization for scalable solutions.
• 5+ years of SQL experience: Advanced skills in SQL, including performance tuning.
• Cloud platform proficiency: Extensive experience with AWS, GCP, or Azure, using Python to automate and optimize cloud infrastructure operations, including resource provisioning, security management, and cost control.
• Data pipeline development: Proven ability to design and maintain scalable, high-performance data pipelines, utilizing tools like Prefect and dbt alongside Python.
• Technical leadership: Ability to work closely with cross-functional teams to translate complex business needs into effective technical solutions, leveraging Python for impactful, data-driven decision-making.
• Data orchestration: Experience in orchestrating ETL and reverse ETL processes using Python, with