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Lead Data Engineer

2 meses atrás


Rio de Janeiro, Brasil Smart Energy Water Tempo inteiro

Company Overview

Choice Technologies, an SEW company, is a business focused in providing revenue assurance solutions for energy utilities, with more than 24 years of experience. Our products (Smart iNTL, Smart iCash, Smart iGEOs and Smart iField) provide a complete solution to mitigate non-technical losses (energy fraud), calculate Energy Balance and increase Cash Collection using machine learning techniques, geospatial technologies and intense process analysis. Our current customers are Utilities companies (Energy, Gas and Water distribution) in Latin America.

We help our customers to achieve their goals to reduce energy losses and increase revenue, by providing our technology, consulting services and R&D projects.


About the role

As a Lead Data Engineer at Choice Tech you will be responsible for designing and implementing the data integration architecture between our customers’ data source systems and Choice solutions. You will be responsible for the full lifecycle of an ETL project, including solution design, development, testing, automation, production delivery, and post-implementation support.


You will work closely with cross-functional teams to ensure the availability, reliability and scalability of our solutions. This role offers the opportunity to lead data matters while contributing to the strategic vision of our data initiatives in conjunction with our other product and delivery team members.


Main responsibilities

  • Data Architecture: Develop and maintain a robust and scalable data architecture that supports the needs of the business.
  • Data Integration: Lead efforts to collect, process, and integrate data from various sources into our solutions.
  • Data Transformation: Design and implement ETL (Extract, Transform, Load) processes to clean, transform, and prepare data for analysis.
  • Data Quality: Ensure data accuracy, consistency, and integrity by implementing data quality checks and monitoring procedures.
  • Team Leadership: Supervise and mentor a team of data engineers and team of delivery, providing guidance and fostering their professional development.
  • Performance Optimization: Continuously optimize data pipelines and processes for improved efficiency and speed.
  • Data Security: Implement and maintain data security and compliance measures to protect sensitive information.
  • Collaboration: Collaborate with data scientists, analysts, and other stakeholders to understand data requirements and deliver actionable insights.
  • Documentation: Create and maintain comprehensive documentation of data engineering processes and systems.
  • Development: Develop, test and implement T-SQL/PL-SQL codes, creating tables, modeling relational and non-relational diagrams. Develops no-SQL routines for unstructured and non-normalized databases.



Requirements

  • Background in Computer Science, Data Engineering or a related field.
  • Previous experience in data engineering and data integration process, with a strong track record of designing and implementing complex data solutions.
  • Proficiency in data warehousing concepts and technologies (e.g., SQL, NoSQL, Snowflake).
  • Strong programming skills in languages such as T-SQL
  • Experience with data pipeline orchestration tools (e.g., Pentaho, Apache NiFi, Jenkins and AWS Glue).
  • Knowledge of data modeling and database design principles.
  • Excellent problem-solving and troubleshooting skills.
  • Strong leadership and team management capabilities.
  • Effective communication skills and the ability to work collaboratively across departments.
  • Experience with product deployment
  • Knowledge of SAP Basis integration
  • Speak English full professional
  • Spanish is a plus
  • Familiarity with big data technologies (e.g., Hadoop, Spark) is a plus.



"Choice Tech, an SEW company, is an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity or expression, pregnancy, age, national origin, disability status, genetic information, protected veteran status, or any other characteristic protected by law."