22 days ago
Remote, United States or San Antonio, TX, USASenior
Base Salary
$130k - $150k/yr
Responsibilities
- Develop scalable data pipelines and integrations for growing data volumes and complexity.
- Build and support a Data Lakehouse for marketing solutions, campaign execution, performance analysis, and benchmarking.
- Collaborate with AI, analytics, data science, business, and engineering teams to improve data models and data accessibility.
- Implement data quality monitoring and processes that ensure production data availability and accuracy.
- Analyze data to troubleshoot issues and support resolution.
- Provide post-deployment production support and resolve unexpected issues.
- Partner with business and engineering teams on long-term data platform architecture strategy.
Requirements
- Bachelor’s degree in Computer Science, Information Technology, or a related field with 5+ years of relevant experience, or a preferred master’s degree in a related field.
- At least 5 years of experience in data engineering, ETL development, or data platform engineering.
- Experience in financial institutions, banking, FinTech, MarTech, AdTech, marketing services, or marketing agencies.
- Experience supporting customer, campaign, audience, marketing performance, attribution, advertising, or transactional data at scale.
- Strong experience with Python and PySpark for production-grade data pipelines.
- Experience designing, building, and supporting Data Lakehouse environments.
- Experience with Apache Airflow, Iceberg, Hive, S3, Trino, and cloud platforms such as AWS, Azure, or GCP.
- Experience with distributed systems, parallel data processing, Spark, Hadoop, Kafka, relational databases, and Linux/Unix-based systems.
- Experience with GitLab, CI/CD processes, Apache Ranger, and Rancher/Kubernetes.
- Experience supporting AI and machine learning applications and understanding their data requirements.
- Strong testing, logging, data observability, analytical, conceptual, problem-solving, and cross-team communication skills.
- Preferred experience building REST APIs and understanding machine learning models and algorithms.
Benefits
- Medical, dental, and vision coverage.
- 401(k) and generous paid time off.
- Life insurance, employee assistance, and pet insurance.
- Applications will be accepted until November 19, 2026, or until a sufficient candidate pool has been identified.
- Compensation depends on factors including skill level, cost of living, experience, and responsibilities.
Tech Stack
Apache AirflowApache HadoopApache HiveApache KafkaApache SparkAWSAzureGoogle Cloud PlatformKubernetesLinuxPythonRancher
Categories
Data Engineering
