Data Engineer

Nasze wymagania: Understands requirements to build, enhance, or integrate data manipulation/automation programs and processes for one or more Acxiom Client solutions and/or applications. Is able to read and interpret application design and functional specifications to write or enhance application code Develops automation jobs for data orchestration, data analysis, and data transfers Using a relevant software language, develops/executes unit test cases and tests software applications that fulfill functional specifications. Documents and interprets test results and corrects application coding errors Provides input on functional requirements and participates/presents code in code review sessions Helps accurately estimate requirements in order to deliver client solutions within time and quality standards Interacts with client/stakeholders to understand and resolve problems in a timely manner, prioritizing multiple issue responses based on the severity of the case Mile widziane: Experience with online and offline data. eg. 3rd party MarTech data (Email send/response, Direct Mail send/response, Prospect Lists) and/or AdTech data (Digital Ad Impressions/Activity, Social, Website activity) Experience working in environments with strong data privacy and data governance Experience working Google Cloud Platform (GCP) ○ VertexAI, Cloud Functions, BigQuery, Workflows, Pub/Sub, Dataflow Hadoop architecture (Cloudera, Hortonworks, MapR) Client facing consulting experience Building reports in Looker, Tableau, or other BI Tools R experience Experience with the SAS programming language O projekcie: The Data Engineer within Analytics Services team in Acxiom will create solutions to business problems defined by specific business requirements. In this position, you will draw upon technical and data processing knowledge to solve complex marketing analytics problems on very large volumes of data. Zakres obowiązków: Experience in data science, engineering, and data analysis. Experience leveraging SQL and Python (dataframes) for data pipeline orchestration, file ingestion, data cleansing, data joining and relationships, data aggregation, data manipulation, and data analysis to create meaningful informed results that drive analytics and reporting Good English language communication skills: Ability to formulate and present insights to both technical and non-technical peers, leaders, and clients Ability to develop creative solutions to abstract analytic problems with minimal guidance on the parameters for the final product Experience troubleshooting and performance tuning data, code, and environmental configurations Excellent understanding of data concepts, data architecture, data manipulation/engineering, and data engineering design An understanding in multiple types of programming languages in order to be adaptable (statically typed vs. dynamically typed and object-oriented vs. procedural) Adaptable – Ability to adapt to diverse technical challenges and systems Multitasker – Ability to prioritize and deliver on multiple projects and tasks that are happening without sacrificing details Team player - Willingness to help others on the team with technical challenges, processes,, and best practices Desire to step beyond basic engineering tasks to understand the underlying data product in the context of the client needs and its significance to the account overall Self-Starter – Ability to manage time and workload effectively without the need for daily check-ins or assignment through project management software