Associate Data Engineer

Full-time

Description

About the Company

East Daley Analytics is a fast-paced leading provider of North American energy infrastructure and commodity market insights, offering data-driven solutions to help clients navigate investment decisions, M&A transactions, and financial market opportunities.

Our Mission

We are moving the market at East Daley. We are doing cool stuff, sitting with the biggest decision-makers in the sector. We love to win! And have fun. When you are on the East Daley Team, you have the opportunity to sit at the table and have a hand in creating your future. We work together with transparency, focus on results, innovation and a play to win attitude.

About the Role

We are seeking a results-driven, detail-oriented Associate Data Engineer to join a best-in-class team. The ideal candidate is an innovative problem solver who is self-motivated and proactive, showing extreme passion for organizing raw data into structured and consumable reports. S/he will have a relentless approach to translating data to drive unique market insights in order ultimately to help clients win. In this position, the Engineer will be able to create structure, in an unstructured and ever-changing environment, with a strong ability to challenge and be challenged in approaches, uses, and organization.

This position represents a rare opportunity to be part of the Core Data Team as a thought leader to build out the company’s data foundation, central to EDA’s strategy and market leadership. Their input and advisement of data sources, intake, processes, and implementation into production will be key to further scale product development and market insights for business stakeholders. The Associate Data Engineer will not only receive mentorship and leadership from the Lead Analyst but will also have unique exposure to C-Suite Executives and the long-term objectives of the business.

This is a full-time, exempt position, based in Greenwood Village, Colorado, and reports to the Lead Analyst of Data Technology.

Requirements

Responsibilities & Requirements

Working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases. As well as advanced knowledge of Python, SSIS, and SSRS are required.

Ingest, clean, normalize, and combine non-uniform, automated, and manual oil and gas fundamental data sources through scraping websites, PDFs, Excel-based models, vendor FTP feeds, and raw miscellaneous data files

Ensure that data is logically paired together in a database and collectively aggregated in a data warehouse

Good understanding of building and designing API’s

Develop, construct, test, and maintain databases and data warehouse architecture that supports the requirements of business stakeholders

Develop dataset processes for data modeling, mining, and production with scheduled deployments and releases in a predictable cadence

Recommend and implement ways to improve data reliability, efficiency, and quality within the data warehouse and for reports

Discover opportunities for new data acquisition

Run queries to produce consumable data and useable reports via.csv and excel for business stakeholders, both on a real-time basis and in a cyclical fashion

Create data tools and interfaces for analytics and team members that assist in building and optimizing products

Intake Analyst adjustments to complex optimization models and calculations to data files and sources on an ongoing basis, feeding back into databases for reporting accuracy and system of records

Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, and re-designing infrastructure for greater scalability

Communicate with both technical and non-technical internal customers to scope business requirements and layout detailed project plans with key milestones and owners

Document all data sources, methodologies, and processes as it relates to the formation and refinement of the database build-out and queries

We are using Predictive Index in our hiring practices, please use this link to take the two PI assessments. Both must be completed:

Qualifications/Education

A minimum of 2 years of experience in technology with a focus on architectural design and planning, data, BI, and/or data warehousing experience

Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases

Experience building and optimizing raw data pipelines, architectures and data sets, with strong analytics skills related to working with unstructured data sets

Machine learning experience and experience with big data infrastructure

Experience performing root cause analysis on internal and external data and processes to answer specific business questions

Proficiency in Microsoft Office Suite

Small to high-growth company experience preferred

Bachelor’s degree in information systems, Computer Information Systems, Engineering, Mathematics or similar field preferred

Oil and Gas industry experience is a plus

Co-Pilot and OpenAI understanding is a plus

Benefits

Medical (with multiple plan options), Dental, and Vision Coverage with Company Contributions

401K with a 3% Company Match

Flexible and Health Savings Account Options with Company Contributions

Life and Accidental Death, Short- and Long-Term Disability Coverage - fully paid by the company

Pay range and compensation package

Salary range is $80,000 - $85,000 plus bonus opportunities depending on experience.

Please note that this job description is not designed to cover or contain a comprehensive listing of activities, duties, or responsibilities that are required of the employee for this job. Duties, responsibilities, and activities may change at any time with or without notice.

Equal Opportunity Statement

East Daley Analytics is an Equal Employment Opportunity (EEO) employer and welcomes all qualified applicants. Applicants will receive fair and impartial consideration without regard to race, sex, color, religion, national origin, age, disability, veteran status, genetic data, or other legally protected status.