Data Engineering & Reporting Manager

This role will lead the development of secure, scalable data pipelines, data lakes, and columnar data warehouse solutions while ensuring a high-performing and reliable data platform. The Manager will work closely with Technology and business partners and directly with the CTO to define and execute the future vision for enterprise data architecture, platform modernization, reporting, and data engineering., Team Leadership & Development

• Lead the Data Engineering team as a hands-on technical manager, combining direct technical contribution with team leadership.
• Provide technical mentorship, architecture guidance, design reviews, and engineering oversight.
• Establish and enforce engineering standards and best practices for architecture, development, testing, documentation, deployment, and production support.
• Develop the technical capabilities of the team through coaching, knowledge sharing, and hands-on collaboration.
• Participate in hiring and developing highly capable data engineering talent as the team scales.

Data Platform Architecture & Engineering

• Serve as the senior technical authority for the Data Engineering team and remain actively involved in architecture, design, development, code reviews, troubleshooting, and technical decision-making.
• Design, implement, and optimize cloud-native data platforms, including data lakes and columnar data warehouses such as Amazon Redshift, Snowflake, or similar technologies.
• Architect, build, and optimize real-time and batch data pipelines supporting structured and semi-structured data.
• Design scalable data models and integration patterns supporting both operational and analytical workloads.
• Write and review complex SQL and provide hands-on expertise in database performance tuning, pipeline optimization, and production troubleshooting.
• Develop proofs of concept to evaluate new technologies, architectural approaches, and data engineering patterns.
• Identify and address technical debt while continuously improving the scalability, reliability, performance, maintainability, and cost efficiency of the data platform.

ETL/ELT & Modern Data Stack

• Drive adoption of modern transformation and orchestration tools such as dbt, AWS Glue, and Apache Airflow
• Lead development of reusable data models and transformation logic
• Ensure observability, lineage, and quality across data pipelines

Architecture Documentation & Standards

• Create and maintain architectural blueprints, data flow diagrams, and design specifications
• Define and document data modeling standards, schemas, and operational workflows
• Promote governance, versioning, and documentation as part of the development lifecycle
• Establish reference architectures, reusable engineering patterns, coding standards, and technical design standards for the Data Engineering team.

Strategic Collaboration

• Partner with Application Development, Security, Infrastructure, and Analytics teams
• Align data engineering efforts with enterprise data strategy and operational goals
• Work directly with the CTO to define and execute future-state data architecture

DevOps and Automation

• Champion DevOps practices within the data engineering team to ensure reliability, repeatability, and speed of delivery
• Maintain CI/CD pipelines and infrastructure-as-code to support scalable deployments
• Implement automated testing, alerting, and monitoring to reduce incident response times and improve platform resilience

Operational Support & On-Call Readiness

• Ensure system availability and responsiveness through monitoring and automation
• Participate in or manage an on-call rotation for critical data pipeline support
• Lead incident response and resolution for data-related production issues

Performance, Metrics, and Reporting

• Define and track KPIs for data platform reliability, pipeline latency, and team delivery
• Provide regular performance updates to executive and business stakeholders, Please note: Symmetry Lending utilizes Automated Decision Systems (ADS) to assist in certain employment-related decisions, which include hiring decisions. However, final hiring decisions are not determined by ADS.

• Bachelor’s degree in Computer Science, Engineering, or a related field is required; Master’s degree preferred
• 10+ years of software or data engineering experience
• 8+ years in data engineering and architecture roles
• 5+ years of technical leadership experience, including leading data engineering teams, architecture initiatives, complex engineering projects, and mentoring engineers
• Strong SQL and performance tuning experience in high-volume environments
• Hands-on experience with Redshift, Snowflake, or similar columnar databases
• Deep understanding of data lake architectures and pipeline orchestration
• Experience with dbt and one or more ETL/ELT tools such as AWS Glue, Apache Airflow, or similar
• Proficient in data modeling for both OLTP and OLAP systems
• Familiarity with CI/CD, Git, Terraform, or similar DevOps tooling
• Demonstrated success working with structured and semi-structured data such as JSON and Parquet
• Demonstrated experience as a hands-on technical leader with the ability to personally architect, design, develop, review, and troubleshoot complex data engineering solutions.
• Expert-level SQL skills with extensive hands-on experience designing, optimizing, and troubleshooting high-volume data workloads.
• Strong hands-on experience designing data architectures, data lakes, data warehouses, data models, and scalable data pipelines.
• Demonstrated experience conducting architecture reviews, technical design reviews, and code reviews.
• Experience developing proofs of concept and evaluating new data technologies and architectural patterns.

Preferred Qualifications

• Experience in the financial industry.
• Strong understanding of data privacy frameworks (e.g., GLBA, CCPA, or GDPR)
• Experience leading migrations and modernization initiatives involving cloud-based data platforms (i.e. AWS, Azure, or GCP).
• Familiarity with data observability and monitoring frameworks
• Proven track record in mentoring and growing high-performing data teams, * Bachelor’s (Required), * Software or Data Engineering: 10 years (Preferred)
• Data Engineering and Architecture: 8 years (Preferred)
• Technical Leadership: 5 years (Preferred)

Symmetry is a fintech infrastructure company that partners with credit unions and banks to run lending programs at scale. Our core business is home equity lines of credit - we manage the full origination, underwriting, capital markets, and servicing lifecycle on behalf of our financial institution partners, who fund and own the loans. We have offices in Atlanta, GA, Denver, CO, and Eden Prairie, MN, and operate coast-to-coast. We take pride in building a diverse team of motivated professionals in a collaborative, fast-moving environment. We offer a competitive benefits package including medical, dental, and vision plan options, paid time off, and more., * 401(k)

• 401(k) matching
• Dental insurance
• Employee assistance program
• Health insurance
• Life insurance
• Paid time off
• Parental leave
• Vision insurance