Job description

Role: Lead-Data Engineering-FTE Location: Richardson, TX - Hybrid Job Summary: We are looking for an experienced Data Engineering to lead and scale our data engineering team in designing, building, and maintaining robust data infrastructure and pipelines. Data Engineer Lead is responsible for designing, implementing, and managing data pipelines and architectures tailored to support AI and machine learning (ML) initiatives. This role will focus on enabling data-driven decision-making by ensuring high-quality, secure, and scalable data systems that align with the firm’s strategic goals. What you’ll do · Architect and implement scalable data solutions using cloud platforms and modern data technologies. · Lead the design, development, and optimization of scalable data pipelines for AI/ML projects. · Collaborate with data scientists and AI teams to ensure efficient data processing and integration. · Collaborate with data scientists, analysts, and business stakeholders to define data models and workflows. · Oversee data quality initiatives, implementing validation rules and automated cleansing processes. · Manage and mentor a team of data engineers, fostering a culture of innovation and continuous improvement. · Evaluate and implement new data technologies to enhance our data engineering capabilities. · Ensure compliance with data security standards and regulatory requirements in the financial sector. · Analyze, review, and alter programs to improve efficiency or adapt to new requirements. · Prepare documentation to describe program development, logic, coding, and corrections. What you’ll need · Bachelor’s degree in information systems, Mathematics, Computer Science, or a related field. · 12+ years of experience in data engineering, at least 5 years in a leadership role. · Proficiency in programming languages like Python · Proficiency in databases like Snowflake, PostgreSQL, Vector DB and SQL Server · Proficiency in data processing tools like Snaplogic, DBT, Spark, Apache Airflow. · Strong knowledge of cloud platforms (e.g., AWS, Azure) and Cloud Services. · Strong knowledge of machine learning frameworks and algorithms. · Solid understanding of data modeling, database management (SQL/NoSQL), and API development. · Experience with data governance and quality management practices. · Excellent communication skills to liaise between technical teams and business Familiarity with data visualization tools and BI platforms. · Knowledge of asset management or financial services is highly desirable.

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