Data Engineer

Title: Data Engineer 3Location: 100% onsite Irving, TXPotential to travel up to 20%Pay: $48-49.33/hr on w2Hours: 8-4:30 Monday through FridayType: ContractLength: 12 months-possibility to extend to 24Screenings: no tech, full panel drug and background once hiredIV process: 1 or 2 rounds+optional benefits, long term contract with ability to extend or convert to full timeEducation & Experience Required:A 4-year degree and/or Master’s degree from an accredited college or university or equivalent experience5-7 years’ experience in data management or data engineering or data operations (data design, data quality, metadata, governance, etc.)Experience with development and delivery of microservices using serverless AWS services (S3, RDS, Aurora, DynamoDB, Lambda, SNS, SQS, Kinesis, IAM)4 year or more of experience in a Cloud environment (AWS, Snowflake)Strong SQL and Python (Desired)Strong AWS experience, including SageMaker, S3, RDS, Cloudwatch and related servicesStrong Snowflake experienceStrong SQL, Python development skillsetUnderstanding of logical data Domains, primarily Customer & Equipment DomainsExperience in Data Operations, Tier 2 Support, or comparable Data Engineering Support roleStrong knowledge of end-to-end data lifecycle across traditional data warehouses, relational databases, operational data stores,business intelligence reporting, and big data analytics.Knowledge of data technology products and components for Big Data and Cloud (AWS, Data Lakes, and similar).Ability to work collaboratively in a complex, rapidly changing, and culturally diverse environment. Soft Skills(Required)Verbal and written communication skills. Ability to clearly communicate complex technical ideasProblem solving skills, customer service and interpersonal skillsAbility to work collaboratively in a complex, rapidly changing, and culturally diverse environment Disqualifiers/Red Flags:If candidate’s location is not on the resume they will be DQ, no exceptions Position’s Contributions to Work Group:Perform all necessary data related tasks which could include data design, data quality, data triage, data governance or data architecture – SQL, Snowflake, AWSDevelop a break/fix solution and address the root cause in the data pipeline implementation/code – Python, AWSDevelop scripts and automation tools to better detect and correct data issues.Develop monitoring and alerting capabilities to proactively detect data issuesWorks directly on complex application/technical problem identification and resolution, including responding to off-shift and weekend support calls.This position will contribute significantly to the efficiency and effectiveness of our data operations, enabling the team to deliver high-quality data solutions and support to various business units. Typical task breakdown:Identify, investigate, and obtain resolution commitments for platform and data issues to maintain and improve the quality and performance of assigned digital product data.Issue Identification: Reports in all forms from customers, dealers, industry representatives, and subsidiaries.Issue Investigation: Statistical analysis, data triage, and infrastructure problem-solving.Issue Resolution: Identify root causes, create SageMaker scripts to fix data, and perform break/fix tasks on data pipeline code.Develop scripts and automation tools to better detect and correct data issues.Develop monitoring and alerting capabilities to proactively detect data issues.Work directly on complex application and technical problem identification and resolution, including responding to off-shift and weekend support calls.Communicate with end users and internal customers to help direct the development, debugging, and testing of application software for accuracy, integrity, interoperability, and completeness.Employee is also responsible for performing other job duties as assigned by (client) management from time to time. Interaction with team:Involve in technical sync up and meetings with internal team including US and offshore teamsLiaise with designers, engineers, and support teams to improve data pipeline performance & reliability. Work environment:Work independently and collaborate with internal team and cross functional teams via Teams meetings, chat, and/or email