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IT Data Engineer

Houston, Texas

Disruptors for a sustainable future

At Anew, we are passionate about delivering meaningful, measurable climate impact in a decarbonizing economy. Inspired by our values of integrity, trust, creativity, and hope, and grounded by decades of experience and unsurpassed knowledge in environmental markets, we make it possible for organizations and communities to thrive while building a sustainable future.

We’re seeking high-energy, creative team players eager to apply their talents to the defining challenge of our time.  If you’re committed to excellence and excited by the prospect of doing well by doing good, we look forward to hearing from you.

General Summary: As a Data Engineer you play a crucial role in evolving the organization's data-driven initiatives. You are the architect and builder of data infrastructure, ensuring that data is collected, stored, processed, and made accessible for analysis, reporting, and machine learning.

Primary Responsibilities and Competencies:

  • Design and Implement ETL/ELT Processes: Build robust Extract, Transform, Load (ETL) or Extract, Load, Transform (ELT) pipelines to move data from various sources (databases, APIs, streaming sources, external data providers) into data warehouses, data lakes, or other data repositories.
  • Develop and Maintain Scalable Data Pipelines: Create efficient and scalable data pipelines to handle large volumes of structured and unstructured data.
  • Automate Data Workflows: Data engineers will write code and scripts to automate repetitive tasks in data collection, processing, and delivery.
  • Monitor and Troubleshoot Pipelines: Continuously monitor pipeline performance, identify and resolve data-related issues, errors, and performance bottlenecks.

Data Architecture and Storage

  • Design and Maintain Data Architecture: Selecting appropriate technologies for data storage such as relational databases, NoSQL databases, data lakes, data warehouses, cloud storage services) and designing efficient data models, schemas.
  • Optimize Data Storage and Retrieval: Work to ensure data is stored in a way that allows for high-performance queries and efficient analytical and operational use cases.
  • Evaluate and Implement Data Solutions: Research and implement new data technologies, tools, and frameworks to improve data infrastructure and processes.
  • Cloud Platform Management: Proficiency in Azure to deploy and manage data solutions in the cloud.

Data Quality, Governance, and Security

  • Ensure Data Quality and Integrity: Implement validation rules, cleansing procedures, and monitoring systems to detect and rectify anomalies, ensuring data accuracy.
  • Implement Data Governance Frameworks: Define standards and policies for data usage, ensuring consistency, reliability, and compliance (e.g., GDPR, HIPAA).
  • Manage Data Security and Access: Implement security controls and access management policies to protect sensitive information from unauthorized access or theft.

Collaboration and Support

  • Provide Data Access Tools: Set up dashboards, analytics tools, and API endpoints to make processed data accessible to end-users and applications.
  • Document Technical Designs and Workflows: Create comprehensive documentation for data pipelines, architecture, and processes to facilitate system transparency.
  • Support Data-Driven Decision Making: By providing clean, reliable, and accessible data, data engineers enable organizations to make informed business decisions.

Skills:

  • Programming Languages: Python, Java, SQL and related technologies
  • Database Systems: Strong knowledge of relational databases (e.g., PostgreSQL, MySQL, SQL Server) and NoSQL databases (e.g., MongoDB, Cassandra).
  • Data Warehousing: Experience with data warehousing and platforms (e.g., Snowflake).
  • ETL Tools: Proficiency with various ETL tools such as snowflake and Databricks
  • Cloud Platforms: Experience with Azure Suite
  • Big Data Technologies: (Hadoop, Spark, Kafka, Hive).
  • Data Modeling and Schema Design: Ability to design efficient data models.
  • Scripting and Automation: For automating data processes.

Equal Employment

Anew is committed to providing equal employment opportunities. All qualified applicants will receive consideration for employment without regard to race, color, ancestry, place of origin, political belief, religion, marital status, family status, physical or mental disability, sex, sexual orientation, gender expression, gender identity, age, or criminal conviction for which a pardon has been granted, or any other protected category under federal, state, provincial and local laws governing workplace discrimination.  

Anew is committed to creating and maintaining a workplace in which all employees have an opportunity to participate and contribute to the success of the business and are valued for their skills, experience, and unique perspectives.

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