Data Engineer – Finance Data & Governance
About The Position
As a Data Engineering, Management & Governance professional, you will build data solutions for ingesting, transforming, and structuring data using vendor and open-source tools to build, migrate, and deploy data pipelines. You will create reusable workflows, build and test scalable pipelines, and support the production deployment and migration of data solutions using cloud architecture principles. The role also supports automated data flows, data governance processes, data quality rules, and compliance policies. Travel may be required. The amount of travel will vary from 0 to 100% depending on business need and client requirements.
Requirements
- At least 3 years of hands-on experience with cloud and big data technologies, such as serverless data processing, Spark/SparkSQL, batch and streaming services, event-driven data pipelines, cloud databases, and programming languages such as Python, SQL, and Node.js.
- At least 3 years of experience with cloud data storage, data management, and data services.
- At least 3 years of experience with data supply chains, including streaming pipelines to address acquiring data, evaluating its value, distilling it, and analyzing it.
- At least 3 years of experience examining data from multiple sources and sharing insights that provide competitive advantage.
- At least 2 years of experience with DevOps and CI/CD processes.
- At least 2 years of experience with scheduling and orchestration.
- Bachelor’s degree or equivalent (minimum 12 years) work experience. With an Associate’s degree, at least 6 years of work experience is required.
Nice To Haves
- Experience in large-scale data integration and data warehouse solutions, Databricks, or Snowflake.
- Ability to lead and effectively facilitate design sessions with business customers and the BI team to derive data requirements and data design information.
- Cloud data-path certifications, such as AWS certifications.
- Business acumen and domain knowledge, such as Finance, Supply Chain, or Sales, to understand nuances in data, collaborate with cross-functional teams, and communicate with leadership teams.
- Understanding of governance and security best practices and organizational policies, procedures, and protocols for regulatory and privacy compliance.
- Basic knowledge of machine learning models and statistical analysis to collaborate with data scientists and business leaders.
- Demonstrable knowledge of artificial intelligence, machine learning, data science, and other relevant technical domains.
Responsibilities
- Apply data engineering principles to create reusable workflows for data ingestion, quality assurance, transformation, and optimization.
- Design, build, and test scalable data pipelines using extract, transform, and load tools, validating outputs against source totals such as financial balances and transaction counts.
- Document requirements and technical design documents.
- Deploy solutions to production environments using CI/CD DevOps and cloud architecture principles.
- Migrate data from legacy data warehouses using cloud architecture principles.
- Automate the flow of data for consumption.
- Build business processes that enable data governance, including stewardship of financial, customer, or product master data.
- Design and advise on data quality rules and establish effective data compliance policies.
Benefits
- Medical coverage
- Dental coverage
- Vision coverage
- Life insurance
- Long-term disability coverage
- 401(k) plan
- Bonus opportunities
- Paid holidays
- Paid time off
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
