We are looking for a Data Solutions Engineer to work in our Data Quality team and engage with both larger Epsilon Engineering, Analytics and Business teams.
This role will be hands on in code development to drive solutions to delivery by effectively engaging with team members across the globe. The person in this role will need to be able to work both independently to meet required specifications of solution delivery and with business users to ingest new complex data quality uses cases. In both cases where the output work product will be incorporated into production environments. The person is involved with managing critical data anomaly detection, integrity checks and overall data quality processing within Conversant. Expertise required in complex Python, Spark, Elasticsearch and API development, as well as, complex SQL queries, data aggregations, data modelling and business intelligence. Ability to understand complex Conversant uses cases and work with business users to translate these uses cases to production data quality detection services.
- You will design and code solutions in both standalone and clustered compute environments to include Hadoop, Spark and Greenplum in Python and Scala.
- On database advanced SQL capabilities for ensuring use case creation and implementation of critical anomaly and integrity checks to enable data driven outlier-detection and decision making for the company’s multi-faceted ad serving operations.
- Working closely with Engineering and Business resources across the globe to ensure enterprise data quality solutions and assets are actionable, accessible and evolving in lockstep with the needs of the ever-changing business model.
- Should be able to develop test cases and validation methodology to demonstrate work product meets required needs.
- Ideal candidate can lead in the areas of: data quality, solution design, code development, data modeling, cross team communication, project management, application maintenance and business facing skills
- Bachelor’s Degree in Computer Science or equivalent degree is required.
- 5+ years of business analysis experience around database marketing technologies and data management with technical understanding in these areas
- Strong experience in SQL and Python
- Experience with Spark, Hadoop and ML
- Experience with scheduling applications with complex interdependencies
- Good experience in working with geographically and culturally diverse teams
- · Familiarity with complex data lake environments that span OLTP, MPP and Hadoop platforms
- Excellent written and verbal communication skills
- Ability to handle complex products
- Excellent Analytical and problem-solving skills
- Ability to diagnose and troubleshoot problems quickly
Epsilon is the leader in outcome-based marketing. We enable marketing that’s built on
proof, not promises.TM Through Epsilon PeopleCloud, the marketing platform for personalizing consumer journeys with performance transparency, Epsilon helps marketers anticipate, activate, and prove measurable business outcomes.
Powered by CORE ID,® the most accurate and stable identity management platform representing 200+ million people, Epsilon’s award-winning data and technology rooted in privacy by design and underpinned by powerful AI. With more than 50 years of experience in personalization and performance working with the world’s top brands, agencies, and publishers, Epsilon is a trusted partner leading CRM, digital media, loyalty, and email programs. Positioned at the core of Publicis Groupe, Epsilon is a global company with over 8,000 employees in over 40 offices around the world. For more information, visit epsilon.com.
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We see a world where modern marketing is built on truth, trust and transparency,
not smoke and mirrors. We want to be part of a world where consumers are
recognized and respected, privacy is protected and integrity is expected.
We enable marketing built on proof, not promises. We create robust customer
experiences that drive performance at the individual level, and help brands make
smarter decisions that drive real business outcomes.