Senior Data Engineer

2 weeks ago

Dallas, United States Optimize Search Group Full time

Job Title: Senior Data Engineer
Duration: Direct Hire
Location: Dallas, TX (Fully On-Site)

Summary/Objective:

The Data Engineer is primarily responsible for resource designing, building, and maintaining our large-scale data infrastructure. This includes data pipelines, ensuring high data quality and accessibility for business intelligence, data warehouse needs and data analytics applications. This position will collaborate with data analysts, BI lead and other stakeholders to understand data requirements and design solutions to support business needs. A high level of expertise in data modeling, ETL processes, and database management/warehousing/data lake will be essential in ensuring the integrity and availability of our organization's data assets.

Essential Functions:

Reasonable accommodation may be made to enable individuals with disabilities to perform these essential functions.

  • Communicate effectively with business leads and stakeholders to shape/define project requirements and objectives.
  • Design, construct, install, test, and maintain reliable and scalable data management systems, including data warehouse needs.
  • Develop and optimize ETL (Extract, transform, load) processes to ensure timely delivery of high-quality data to downstream applications and analytics platforms.
  • Ensure systems meet business requirements and industry best practices for data architecture and processing.
  • Develop processes for data modeling and data production for downstream consumption.
  • Integrate new data management technologies and processes as well as software engineering best practices into existing structures and processes.
  • Create custom software components and analytics applications when necessary.
  • Employ a variety of languages (primarily Python and SQL) and tools to marry systems together.
  • Recommend ways to improve data reliability, efficiency, and quality.
  • Collaborate with data architects, modelers, and IT team members on project goals.
  • Mentor more junior data talent, fostering a culture of continuous improvement in data practices.
  • Actively participate with application end users and IT teams to support system upgrades, new processes, and initiatives.
  • Advocate within project design meetings to ensure all requirements are documented and accounted for.
  • Lead user acceptance testing and end-to-end testing including end-user training.
  • Provide monitoring and troubleshooting of integration points between the ERP system and external applications/API usage.
  • Drive continuous improvement and challenge paradigms that may be barriers to progress.
  • Assist in maintaining system standards, security and cleanliness of incoming data.
  • Advise, develop and standup Data Warehouse - capturing data needs across business units and departments.
Competencies:
  • Self-starter able to work with little supervision.
  • Proven analytical and problem-solving abilities
  • Ability to diagnose and solve problems creatively.
  • Demonstrated knowledge of Microsoft Office products and SQL development
  • Comfortable working across multiple ERP systems with the mindset of automation and cross system analytics, business approaches and comprehensive SOPs/documentation.
Work Environment:
Primarily in an office setting, with occasional meetings or training sessions in other areas of the company.

Physical Demands:
Moderate physical demands, including sitting for extended periods and occasional light lifting of IT Materials

Travel Required:
Negligible travel required.

Required Education and Experience:
  • Bachelor's degree in computer science, Engineering, or related field; Master's degree or equivalent experience preferred.
  • Advanced knowledge of SQL and experience with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.
  • Experience building and optimizing data pipelines, architectures, and data sets for analytics.
  • Strong analytic skills related to working with both structured and unstructured data assets.
  • Experience with modern data tools: Snowflake, BigQuery, dbt, Airflow, dagster, Fivetran etc.
  • Experience with cloud services: AWS, Azure, GCP, etc.
  • Strong project management and organizational skills.
  • Excellent communication and collaboration skills.

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