What are the responsibilities and job description for the Data Engineer position at World Finance?
Full job description
The Data Engineer will design, develop, and optimize data pipelines, storage solutions, and integrations that support enterprise-wide data operations. This role collaborates with data architects, engineers, and cross-functional teams (e.g., marketing, analytics, operations, software engineering) to ensure secure, scalable, and efficient data infrastructure. With expertise in data warehousing, cloud platforms (Snowflake, AWS, Databricks), and ETL processes, the Data Engineer will enhance data-driven decision-making and streamline business operations.
Essential Duties and Responsibilities:
Protect confidential company information.
Develop, maintain, and optimize data pipelines to support secure and efficient data movement across systems.
Implement and refine ETL/ELT workflows for structured and unstructured data, ensuring scalability and performance.
Model and assemble data sets that meet functional and technical business requirements.
Collaborate with stakeholders to define data requirements and deliver solutions aligned with business objectives.
Ensure data integrity, security, and governance across all platforms.
Process file-based data extracts using data retrieval and management tools to provide timely loading of critical business data.
Identify and implement process automation to improve data workflows and reduce manual intervention.
Integrate external and internal systems to enhance data availability and usability.
Communicate effectively with non-technical stakeholders to translate business needs into technical solutions.
Qualifications:
To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required:
Expertise in SQL and relational databases (e.g., PostgreSQL, MS SQL Server, Snowflake).
Experience designing and optimizing data warehouses and large-scale data processing systems.
Strong proficiency in ETL/ELT development and tools (e.g., Airflow, ADF, Matillion, Fivetran, SSIS).
Experience with cloud-based data platforms (e.g., Snowflake, Databricks, AWS Redshift, Google BigQuery, Azure Data Lake).
Strong programming skills in Python, Scala, or similar languages for data processing and automation.
Familiarity with data modeling techniques (dimensional modeling, Data Vault, normalization/denormalization).
Knowledge of data governance, security, and compliance best practices.
Ability to troubleshoot and optimize data pipelines, queries, and storage performance.
Experience with business intelligence and reporting tools (e.g., Power BI, Looker, Tableau) is a plus.
Ability to translate business needs into technical solutions and communicate complex ideas to non-technical stakeholders.
Strong analytical and problem-solving skills.
Education and/or Experience:
Strong programming skills in Python, Scala, or similar languages for data processing and automation.
Familiarity with data modeling techniques (dimensional modeling, Data Vault, normalization/denormalization).
Knowledge of data governance, security, and compliance best practices.
Ability to troubleshoot and optimize data pipelines, queries, and storage performance.
Experience with business intelligence and reporting tools (e.g., Power BI, Looker, Tableau) is a plus.
Ability to translate business needs into technical solutions and
Deep expertise in Azure services, including Azure SQL Database, Azure Data Lake, and Azure Data Factory.
Physical Demands:
Must be able to constantly remain in a stationary position.
The person in this position needs to occasionally move about inside the office to access file cabinets, office machinery, etc.
Constantly operates a computer and other office productivity machinery, such as a calculator, copy machine, and computer printer.
Occasionally may require light lifting to 25 pounds.
Work Environment:
Office environment.
Occasional travel may be required.
