Senior Software Engineer - Data Engineering
About The Position
We are seeking an experienced and strategic Senior Software Engineer - Data Engineering to lead the design, development, and optimization of our enterprise-scale data infrastructure. In this role, you will architect and champion highly scalable, secure, and cost-effective data systems that power analytics, reporting, ML, and data products across the organization. This role combines hands-on technical leadership, cross-functional influence, platform ownership, and mentorship of engineering teams. You’ll be a core contributor to our long-term data strategy, execution, and operational excellence. As a Staff Data Engineer, you will work closely with engineering leadership, data scientists, analysts, product managers, and stakeholders to translate business needs into robust, production-grade data solutions. Platform & Strategy Impact: You won’t just write pipelines — you’ll define how data is built, shared, governed, and evolved across the company. Leadership Beyond Code: Influence engineering standards, technology choices, and business outcomes. Cross-Team Visibility: Work with diverse teams from analytics to product to executive leadership. Ownership & Autonomy: Champion initiatives from architectural plans through deployment and live operations.
Requirements
- 10+ years of professional experience in data engineering, software engineering, or related fields.
- Proven experience architecting large-scale data platforms used for analytics, operational reporting, and ML/AI.
- Deep expertise in designing and building scalable ETL/ELT pipelines, data warehouses, and data lakes.
- Strong background in distributed data processing (e.g., Spark, Flink, Hadoop) and realtime systems (e.g., Kafka, Kinesis).
- Demonstrated success owning engineering workstreams end-to-end (design → deployment → operational support).
- Advanced proficiency in SQL and at least one programming language (Python, Java, Scala).
- Experience with cloud data platforms and infrastructure (AWS preferred: Redshift, S3, Glue, Lambda, EMR, Athena, Kinesis).
- Data modeling expertise (dimensional, star/snowflake schemas, OLAP design).
- Strong understanding of data governance, quality frameworks, and metadata practices.
- Hands-on experience with orchestration tools (e.g., Airflow, dbt, or similar).
- Exceptional problem-solving, analytical, and strategic thinking skills.
- Excellent written and verbal communication; capable of translating complex concepts for technical and non-technical audiences.
- Track record of influencing technical direction and collaborating with senior leadership.
- Must be able to demonstrate lawful ability to work in the United States
Nice To Haves
- Master’s degree or higher in Computer Science, Engineering, Mathematics, or related field.
- Experience in highly regulated or consumer-facing environments with strong security and compliance needs.
- Prior experience mentoring across teams and shaping engineering culture.
- Familiarity with containerization, CI/CD, IaC (Terraform/CloudFormation), and observability tools.
Responsibilities
- Lead the architecture, design, and implementation of scalable data platforms (data lakes, warehouses, streaming, OLAP/OLTP stores).
- Define and own end-to-end data pipeline frameworks for real-time and batch data ingestion, processing, transformation, and serving.
- Establish reusable frameworks and abstraction layers that increase development velocity and reduce operational risk.
- Drive long-term strategy for data infrastructure, tooling, and processes aligned with business goals.
- Act as technical authority and point of escalation for complex data engineering challenges.
- Set standards for engineering excellence (code quality, architecture, performance, security, observability, and cost-efficiency).
- Partner with product and business teams to understand analytic and operational requirements and translate them into deliverables.
- Collaborate with data scientists and ML engineers to productionize models and analytics.
- Influence cross-team prioritization and roadmap decisions through technical insight and business impact.
- Build and enforce robust practices for monitoring, alerting, quality, change management, and incident response.
- Ensure data accuracy, reliability, lineage, and compliance across data workflows.
- Lead architectural capacity planning, performance tuning, and cost optimization initiatives.
- Coach and mentor senior and mid-level data engineers; provide technical reviews and guidance.
- Help build a strong engineering culture focused on collaboration, learning, and high-quality delivery.
Benefits
- Competitive salary packages
- Comprehensive medical, dental, vision, and life insurance benefits for you and your family
- Flex PTO for exempt employees and competitive PTO for non-exempt
- Paid parental leave for eligible employees
- 401(k) matching
- Tuition reimbursement on approved programs
- Great health & well-being benefits including Teladoc for general medical and mental health care
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What This Job Offers
Job Type
Full-time
Career Level
Senior
