What are the responsibilities and job description for the Data Engineer position at Warwick Investment Group?
FIRM INTRODUCTION
Warwick Group is a private equity firm that invests in real assets. At Warwick we strive to couple innovative techniques in data mining and machine learning to make intelligent data-driven investment decisions.
Data is deeply embedded in the culture at Warwick. Every department uses data in different varieties and volumes. We rely on public and private data – lots of it – to improve asset identification and management and continuously evaluate risk.
As a Data Engineer within the Data Science & Engineering team, you will take an essential role in building scalable, repeatable, highly available and secure data pipelines. This is a unique opportunity to work with a talented group founded with the goal of applying cutting-edge technology to rich data for improving investment strategies.
We're looking for a talented Data Engineer with extensive experience in building scalable data pipelines to join us as a foundational member of the team and to provide leadership in all areas that relate to data integration and data management.
JOB RESPONSIBILTIES
- Facilitate acquisition of data from a variety of different sources and analyzing the data for correctness with input from downstream users
- Work with various structured and unstructured data systems (relational, file based, HDFS/ADLS) and their performance tuning requirements
- Develop automation tools where appropriate, with a focus on collecting, parsing and managing large sets of discrete data sources
- Data-modeling and master data management
- Building data services for applications and machine learning/analytics pipelines using GraphQL, Apollo, Hasura, or REST AI.
- Review business requirements, recommending technological solutions that can be integrated and deployed in the environment
- Identify key opportunities for redesign of systems infrastructure to meet end user needs
QUALIFICATIONS
- Bachelor’s / Master’s Degree (preferably in Computer science or equivalent)
- 5 years of work experience in Data Engineering or another relevant field
- Solid understanding of database design principles and the system development life cycle
- Ability to communicate and understand end user or business requirements
- Strong familiarity with Microsoft SQL Server, Sybase, Oracle, ETL Tasks, SSIS, Database Development and Administration
- Experience in data acquisition from REST API, SFTP, Cloud Storage, web scraping
- Experience with self-service data delivery platforms like Dremio or equivalent
- Familiarity with orchestration using Airflow/Prefect, SQL Server
- Development in SQL, Python, JavaScript, and Open-Source technologies
- Experience working in secure cloud platforms Azure, AWS, GCP
- Comfortable working in both Windows and Linux environments
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