Senior Data Engineer
At a glance
Senior Data Engineering role at Candidate Experience site (CX). Dallas · full-time · no salary stated · we estimate $142,375–$192,500 across the United States.
Candidate Experience site (CX) has not published a salary for this role. The figure below is our estimate, not theirs.
dataroles summary, based on the employer's posting.
What you'll do
- Build and maintain ingestion, discovery, and consumption pipelines for file feeds, APIs, change-data capture, and streaming
- Bring new sources online by mapping fields, managing types, adding enrichment, and setting quality and privacy rules
- Work with product owners, engineering leads, and data stewards to turn business priorities into pipeline requirements
- Extend reporting data models, test pipeline changes, and support deployment through CI/CD and DevOps practices
- Monitor production pipelines, investigate processing issues, and keep operational runbooks and platform documentation current
What you bring
- A computer science degree or equivalent experience, plus at least five years programming with an advanced object-oriented language
- At least four years using SQL for high-volume processing and ETL, with data quality and testing practices
- Three or more years designing and implementing cloud data warehouses or Lakehouses
- Hands-on familiarity with event-driven ingestion, Lakehouse table formats, CI/CD, infrastructure as code, and Agile
Who this fits
This senior engineering role suits you if you can build reliable data pipelines and translate business requirements into tested platform changes. The work includes production monitoring, documentation, and collaboration with product, engineering, and data stewardship teams.
From the employer
Cetera Financial Group is looking for a motivated, innovative data engineer to help shape and extend our data estate as we build the future of fintech. Our modern, cloud-native and AI-enabled data platform optimizes speed, scale and quality with a contemporary design that leverages governed data contracts to drive intelligent, flexible and resilient data pipelines.
This opportunity requires experience with Lakehouse architecture, cloud-native integration patterns, and expertise with the latest data engineering best practices to deliver clean, automated, well-documented and auditable data products for enterprise consumers and analytics. This collaborative role works closely with product owners and engineering leads to translate business and regulatory needs, including data ingestion, lineage, PII protection, and quality goals, into an automated future-forward data platform using AI-powered software engineering to develop secure, extensible and well-tested code within an enterprise data ecosystem.
Responsibilities
Key responsibilities include:
- Design, build and maintain data ingestion, discovery and consumption pipelines across file-based feeds, APIs, change-data-capture and streaming sources, driven by reusable, declarative data contracts
- Collaborate with product owners, engineering leads and data stewards to gather and implement requirements, ensuring data pipelines and contracts reflect prioritized business imperatives
- Own the onboarding of new data sources end-to-end through pipeline development, field mapping, type management, enrichment and quality/privacy rule definitions
- Work with orchestration and metadata systems to process event, dependency and schedule-driven activities
- Support and extend the downstream data models that power business intelligence and reporting
- Apply modern software engineering practices to ensure pipeline changes are well-specified and production ready, backed by automated unit and end-to-end tests
- Use AI-assisted development tools for coding, testing and documentation, while staying accountable for correctness, security and sound architecture
- Participate in CI/CD and DevOps best practices for data platform development, validation and deployment
- Monitor pipeline health and data processing in production, troubleshooting and routing issues to the appropriate remediation process
- Maintain documentation, including operational runbooks, to capture and share data platform knowledge and insights
Experience & Education
- Bachelor’s degree in computer science or equivalent experience
- 5+ years of programming experience with an advanced, object-oriented language (Python preferred)
- 4+ years of hands-on experience with SQL, writing efficient code for high-volume data processing and supporting high-performing ETL processes, including data quality and testing practices
- 3+ years of hands-on experience with data warehousing/Lakehouse design and implementation on cloud-based platforms (e.g. AWS, Databricks, Snowflake)
- Experience with event-driven data ingestion patterns and Lakehouse table formats (e.g. Apache Iceberg)
- Experience with CI/CD and infrastructure-as-code practices
- Experience with Agile development methodologies
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