Senior Data Engineer

At Acxiom, our vision is to transform data into value for everyone. Our data products and analytical services enable marketers to recognize, better understand, and then deliver highly applicable messages to consumers across any available channel. Our solutions enable true people-based marketing with identity resolution and rich descriptive and predictive audience segmentation. We are seeking an experienced Data Engineer with a versatile skill set to undertake data engineering efforts to build the next-generation ML infrastructure for Acxiom’s business.

As part of the Data Science and Analytics Team, the Sr. Data engineer will partner with Data Scientists, work hands-on with Big Data technologies and build scalable data pipelines/infrastructure to support development of health care propensity models. The Sr. Data engineer’s responsibilities include collaborating with internal and external stakeholders to identify data ingestion, processing, ETL, data warehousing requirements and develop appropriate solutions using modern data engineering stack in cloud. Success in this role comes from combining a strong data engineering background with product and business acumen to deliver scalable data pipeline and database solutions that can enable & support a high performant, large scale modeling infrastructure at Acxiom. The Sr. Data Engineer will be a champion of the latest Cloud database technologies & data engineering tools.

What you will do:

• Partner with Cloud Architects, Data scientists to build scalable, next generation data pipelines for health care model development, model management and governance in Cloud
• Be a thought leader and champion for adoption of new cloud-based database technologies and enable migration to new cloud-based modeling stack
• Collaborate with other data scientists and team leads to define project requirements & build the next generation data source ingestion, ETL, data pipelining, data warehousing solutions in Cloud
• Build data-engineering solutions by developing strong understanding of business and product data needs.
• Develop close partnership with internal stakeholders and partners from Engineering, product, and business
• Build expert knowledge across various data sources– Acxiom health data sources, Acxiom proprietary data (demographics, psychographics, lifestyle segments), Survey/Panel data, media content activity (TV, Digital, Mobile), and product purchase or transaction data and develop solutions for seamless ingestion and process of the data
• Resolves defects/bugs in data pipelines during QA testing, pre-production, production, and post-release.
• Contributes to the design and architecture of services across the data landscape
• Participation in development of the integration team, contributing to reviews of methodologies, standards, and processes.
• Comprehensive internal documentation of designs and service components

Required Skills:

• 6+ years of data engineering experience with at least 4+ years’ experience working with healthcare data sources and developing large scale data pipelines in healthcare vertical.
• Strong background in data pipelining, warehousing, ETL development solutions for data science and other Big Data applications
• 6+ years working with large scale terabyte scale data sources. Ability to work independently, understand & develop complex data solutions
• Knowledge of ML algorithms, model development processes and prior experience creating data solutions to support large scale modeling efforts.
• Experience with distributed, columnar and/or analytic oriented databases or distributed data processing frameworks.
• Minimum of 3 years of experience with Cloud databases – AWS Redshift, Snowflake, Azure SQL database, Google Cloud SQL or similar. Experience with NoSQL databases such as mongoDB, Cassandra or similar is a plus
• Minimum of 4 years of experience in developing data ingestion, data processing and analytical pipelines for big data, relational databases, NoSQL, data lake and data warehouse solutions
• Minimum of 4 years of hands-on experience in Big Data technologies such as, PySpark, Spark/SparkSQL, Dask or similar distributed compute frameworks. Knowledge of streaming technologies such as Kafka, Spark Streaming Ingestion API is a plus
• Strong programming skills using Python, PySpark, Scala, Java or similar
• Experience with container-based application deployment frameworks (Kubernetes, Docker, ECS/EKS or similar)
• Experience with Data Visualization tools such as Tableau, Looker or similar
• Outstanding troubleshooting, attention to detail, and communication skills (verbal/written) in a fast paced setting.
• Bachelor’s degree in computer science or relevant discipline or 6-7 years of relevant work experience.

• Solid commun