
5001 - 10000 employees
đŁ Marketing
đ¸ Finance
đł Fintech
Marketing ⢠Finance ⢠Fintech
Vericast is a company focused on accelerating the performance of financial institutions. Through the use of data, artificial intelligence, and innovative strategies, Vericast helps banks and credit unions drive growth and enhance their marketing performance. The company provides a variety of solutions including digital marketing, direct mail, card solutions, check solutions, customer and employee insights, and customer change management. Vericast leverages responsibly sourced data to engage consumers effectively, which is why many financial institutions trust them for solving marketing challenges. Their expertise in the financial sector is aimed at delivering insights and growth solutions, positioning them as a leader in financial marketing services.
đ October 20
đ¤ Texas â Remote
đľ $130k - $150k / year
â° Full Time
đ Senior
đ° Data Engineer
đť Ghost score 0%
Airflow
Apache
AWS
Azure
Cloud
Distributed Systems
ETL
Google Cloud Platform
Hadoop
Kafka
Kubernetes
Linux
PySpark
Python
Spark
Unix
Where this job comes from
Posted on Vericast's careers page, not through a job board
First seen by Remote Rocketship October 20
Still open on Vericast's site. Checked 1 hour ago.

5001 - 10000 employees
đŁ Marketing
đ¸ Finance
đł Fintech
Marketing ⢠Finance ⢠Fintech
Vericast is a company focused on accelerating the performance of financial institutions. Through the use of data, artificial intelligence, and innovative strategies, Vericast helps banks and credit unions drive growth and enhance their marketing performance. The company provides a variety of solutions including digital marketing, direct mail, card solutions, check solutions, customer and employee insights, and customer change management. Vericast leverages responsibly sourced data to engage consumers effectively, which is why many financial institutions trust them for solving marketing challenges. Their expertise in the financial sector is aimed at delivering insights and growth solutions, positioning them as a leader in financial marketing services.
⢠Develop scalable data pipelines and build new integrations to support continued growth in data volume and complexity ⢠Build a robust Data Lakehouse supporting Vericast's marketing solutions business and financial institution clients ⢠Support pre-sales, campaign execution, campaign performance analysis, and benchmarking ⢠Collaborate with AI, Analytics, and business teams to improve data models feeding AI and analytics tools ⢠Implement processes and systems to monitor data quality and ensure production data availability and accuracy ⢠Perform data analysis to troubleshoot data-related issues and support resolution ⢠Provide post-deployment support and quickly resolve unexpected production issues ⢠Partner with business units and engineering teams to shape long-term data platform architecture strategy
⢠Bachelor's degree in Computer Science, Information Technology, or a related field, with 5+ years of relevant experience; or Master's degree in Computer Science, Information Technology, or a related field (preferred) ⢠5+ years of experience in Data Engineering, ETL development, or Data Platform Engineering ⢠Experience working within a Financial Institution (FI), Banking, FinTech, MarTech, AdTech, Marketing Services, or Marketing Agency environment ⢠Experience supporting customer, campaign, audience, marketing performance, attribution, advertising, or transactional data at scale ⢠Strong experience with Python and PySpark for building production-grade data pipelines ⢠Experience designing, building, and supporting Data Lakehouse environments ⢠Experience with Apache Airflow, Iceberg, Hive, S3, and Trino ⢠Experience with cloud platforms such as AWS, Azure, or GCP ⢠Experience with Agile software development methodologies ⢠Experience with GitLab and CI/CD processes ⢠Experience supporting AI and machine learning applications ⢠Understanding of machine learning models and data requirements for Data Science teams ⢠Experience with distributed systems and parallel data processing using Spark, PySpark, Hadoop, Kafka, and Hive ⢠Proficiency with relational databases ⢠Strong knowledge of Linux/Unix-based systems ⢠Hands-on experience with Apache Ranger and Rancher/Kubernetes ⢠Excellent analytical, conceptual, and problem-solving skills ⢠Strong communication skills that promote cross-team collaboration
⢠Medical coverage ⢠Dental coverage ⢠Vision coverage ⢠401K ⢠Generous PTO allowance ⢠Life insurance ⢠Employee assistance ⢠Pet insurance
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