Data Analytics Engineer
About The Position
The Data Analytics Engineer will be part of the Data Engineering team whose primary mission is to build trusted Data Ingestion Pipelines to seamlessly move and transform data from SaaS and in house transactional databases to a Data Warehouse to enable actionable business insights. The data in the Warehouse will serve as a foundation for Reporting, Machine Learning Analysis and Generative AI. The ideal candidate will be a strong technical resource with effective communication and leadership skills to be a member of data engineering team. The role requires collaboration with cross functional teams and ability to play multiple roles depending upon the situation. The ideal candidate should have strong bias for action, able to dig into details when requirements are fuzzy and have a passion to push forward to progress. If you are an ambitious technologist who is looking to grow, and who is passionate about building world-class products and technology, we encourage you to apply for this exciting opportunity.
Requirements
- BS in Engineering, Business Administration, Statistics, Business Analytics, or applicable experience in related field
- Minimum of (3) three years of SDLC experience in ETL/ELT environments with tools/technologies such as Fivetran, dbt, SQL, AWS Redshift, Boomi, PowerBI , Git.
- Minimum of (2) years of experience in building out schemas for Analytical purposes.
- Minimum (1) years of hands on experience AWS Cloud and Services such as AWS Glue, AWS Lambda, Python.
- Familiar with ERP, CRM products such as Salesforce, NetSuite, Hubspot and Eloqua.
- Strong development background and expert level skills with modern SDLC best practices.
- Proven track record of delivering successful data initiatives.
- Excellent communication and interpersonal skills, with the ability to build strong relationships with internal and external stakeholders.
- Strong analytical and problem-solving skills, with the ability to make data-driven decisions.
- Experience working in a fast-paced, agile environment.
- Ability to prioritize and manage multiple projects simultaneously.
Responsibilities
- Implementation of data ingestion pipelines following the guidelines and best practices defined.
- Implement data mapping, data transformation, automated testing and data validation.
- Contribute and implement standards and best practices within the Data Engineering Team.
- Write detailed stories, sprint grooming and actively contribute in the Agile software development life cycle.
- Accountable for Delivery and 100% uptime of the Environments.
- Collaborate with cross-functional teams, including ecosystem leadership and data insights teams, engineering, sales, and marketing to ensure all stakeholders are aligned.
- Partner with scrum master daily to provide updates.
- Partner with Data Insights team on a daily basis to stay aligned on priorities.
- Stay up to date with the latest industry trends and emerging technologies to identify opportunities for innovation and growth.
- Establish and maintain effective communication channels with internal and external stakeholders.
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
