Senior Data Engineer

This is a fully remote position, open to applicants in Texas.

📋 Description

• Design and implement scalable data pipelines while creating new integrations to accommodate the increasing volume and complexity of data.

• Establish a reliable Data Lakehouse to support Vericast's marketing solutions and financial institution clients.

• Assist in pre-sales activities, campaign execution, performance analysis, and benchmarking efforts.

• Work collaboratively with AI, Analytics, and business teams to enhance the data models that supply information to AI and analytics tools.

• Develop processes and systems to monitor data quality, ensuring production data is accurate and readily available.

• Conduct data analysis to diagnose data-related issues and facilitate their resolution.

• Offer post-deployment support and address any unexpected production challenges.

• Collaborate with business units and engineering teams to define the long-term strategy for the data platform architecture.

⛳️ Requirements

• A Bachelor's degree in Computer Science, Information Technology, or a related field, accompanied by 5+ years of pertinent experience; or a Master's degree in the same fields (preferred).

• Over 5 years of experience in Data Engineering, ETL development, or Data Platform Engineering.

• Familiarity with working in a Financial Institution (FI), Banking, FinTech, MarTech, AdTech, Marketing Services, or Marketing Agency setting.

• Experience in managing customer, campaign, audience, marketing performance, attribution, advertising, or transactional data at scale.

• Proficient in Python and PySpark for the development of production-grade data pipelines.

• Skilled in designing, developing, and maintaining Data Lakehouse environments.

• Experience with tools such as Apache Airflow, Iceberg, Hive, S3, and Trino.

• Knowledge of cloud platforms including AWS, Azure, or GCP.

• Familiarity with Agile software development methodologies.

• Experience with GitLab and CI/CD practices.

• Background in supporting AI and machine learning applications.

• Understanding of machine learning models and the data requirements to support Data Science teams.

• Preferred experience in building REST APIs.

• Strong programming capabilities in Python and PySpark, including testing, logging, and data observability.

• Experience with distributed systems and parallel data processing using Spark, PySpark, Hadoop, Kafka, and Hive.

• Proficiency in relational databases.

• Solid understanding of Linux/Unix-based systems.

• Practical experience with Apache Ranger and Rancher/Kubernetes.

• Exceptional analytical, conceptual, and problem-solving abilities.

• Strong communication skills that foster collaboration across teams.

🏝️ Benefits

• Medical coverage

• Dental coverage

• Vision coverage

• 401K

• Generous PTO allowance

• Life insurance

• Employee assistance

• Pet insurance