Data Engineer Master

texascapitalbank; Richardson (TX); On-site; USD 120,000 - 170,000; Full time

Benefits offered by this job

Health insurance

Wellness program

Fertility benefits

Life insurance

Disability insurance

401K match

Paid leave

Paid holidays

PTO

Job summary

Texas Capital Bank seeks a skilled Data Engineer Master to design and maintain data systems powering reporting, analytics, and AI initiatives. You will collaborate with cross-functional teams to ensure data quality and efficient data workflows across the bank.

The role calls for deep expertise in SQL, data platforms, and at least one data engineering language (Python/Scala/Java), with a focus on scalable, secure data solutions and continuous improvement.

Qualifications

• 8+ years of relevant experience in data engineering or a related field.
• Bachelor's degree in Computer Science, Engineering, Information Systems or Technology, or related field.
• Strong SQL and hands-on coding in at least one data engineering language (Python, Scala, Java).
• Experience with diverse data platforms, operating systems, cloud solutions, and architectural concepts.

Responsibilities

• Design, construct, and maintain data collection, storage, access and analytics systems.
• Design and build batch and streaming pipelines across structured, semi-structured, and unstructured data.
• Collaborate with cross-functional teams to ensure data quality and drive data-driven decision making.
• Embed data quality, lineage, and automated testing into delivery as code; support AI/ML data needs.
• Mentor other engineers and promote best practices in data engineering.

Skills

SQL

Python

Java

Scala

Education

Bachelor's degree in CS/Engineering/IS

Tools

Data warehouse

Lakehouse

Job description

Texas Capital is built to help businesses and their leaders. Our depth of knowledge and expertise allows us to bring the best of the big firms at a scale that works for our clients, with highly experienced bankers who truly invest in people's success - today and tomorrow.

While we are rooted in core financial products, we are differentiated by our approach. Our bankers are seasoned financial experts who possess deep experience across a multitude of industries. Equally important, they bring commitment - investing the time and resources to understand our clients' immediate needs, identify market opportunities and meet long-term objectives . At Texas Capital, we do more than build business success. We build long-lasting relationships.

Texas Capital provides a variety of benefits to colleagues, including health insurance coverage, wellness program, fertility and family building aids, life and disability insurance, retirement savings plans with a generous 401K match, paid leave programs, paid holidays, and paid time off (PTO).

• health insurance coverage
• wellness program
• fertility and family building aids
• life and disability insurance
• retirement savings plans with a generous 401K match
• paid leave programs
• paid holidays
• paid time off (PTO).

Headquartered in Dallas with offices in Austin, Fort Worth, Houston, Richardson, Plano and San Antonio, Texas Capital was recently named Best Regional Bank in 2024 by Bankrate and was named to The Dallas Morning News ' Dallas-Fort Worth metroplex Top Workplaces 2023 and GoBankingRate's 2023 list of Best Regional Banks. For more information about joining our team, please visit us at www.texascapitalbank.com .

The Data Engineer Master is responsible for designing, constructing, and maintaining systems for data collection, storage, access, and analytics at Texas Capital Bank - including the data foundations that power reporting, advanced analytics, and AI. The successful candidate will collaborate with cross-functional teams to ensure data quality, optimize data workflows, and drive data driven decision making across the firm.

We are seeking qualified candidates with a passion for innovation that have extraordinary levels of critical thinking, motivation, and initiative and aspire to deliver superior client experiences.

Responsibilities

• Practical application of engineering science and technology, including applying principles, techniques, procedures, and equipment to the design and implementation of data warehouse and advanced analytical applications.
• Responsible for enhancing and maintaining TC's data warehouse, lakehouse, and analytical platforms.
• Design and build batch and streaming pipelines across structured, semi-structured, and unstructured data.
• Support the engineering needs associated with advanced analytical capabilities (machine learning, predictive modeling, artificial intelligence), including training data, feature pipelines, and the retrieval and search data layers behind AI applications.
• Embed data quality, validation, lineage, and automated testing into delivery as code; leverage debugging and testing processes and protocols to finalize code.
• Perform new feature exploration of each solution to determine feature-fit for strategic and tactical program activities.
• Address planned and unplanned production issues, including monitoring of pipeline and application performance, maintenance, coordination, communication, and business support.
• Document and implement change control and best practices with regards to system maintenance, configuration, development, testing, and data integrity.
• Collaborate with other members of the engineering team to design new features.
• Identify areas for process, efficiency, and platform cost improvement.
• Perpetual improvement of data engineering practices to automate manual processes, including use of AI-assisted development tooling within the bank's review, security, and change management standards.
• Partner with PMO team to run the Agile processes.
• Provide end-to-end solutions for LOBs.
• Lead the craftsmanship, availability, resilience, and scalability of your solutions.
• Bring a passion to stay on top of tech trends, experiment with and learn new technologies, participate in internal & external technology communities, and mentor other members of the engineering community.
• Encourage innovation, implementation of cutting-edge technologies, inclusion, outside-of-the-box thinking, teamwork, self-organization, and diversity.

Qualifications

• Minimum 8 years of relevant experience in an appropriate technology domain.
• Bachelor's degree in Computer Science, Engineering, Information Systems or Technology, or related field.
• Advanced knowledge of the practical application of engineering science and technology, including data management principles, techniques, procedures, and equipment to the design and implementation of products.
• Advanced understanding of SQL and hands-on coding in at least one data engineering language (Python, Scala, Java).
• Advanced knowledge and understanding of diverse data platforms, operating systems, cloud solutions, current and emerging technologies.
• Knowledge of architecture and development