Data Engineer

Responsibilities: Design, develop and operationalize data pipelines for batch, streaming and event-based processing Create and review conceptual, logical, and physical data models for transactional and analytical use cases Design and implement data processes to support DW, ODS, Data Lake, Lakehouse architectural patterns Use open-source and proprietary technologies on the cloud to solve for common data engineering problems Perform data analysis to solve for complex and unique business problems Evaluate data quality for existing use cases and implement improvements Conduct quality assurance (QA) to ensure reliability and accuracy of solutions before production releases Troubleshoot and resolve production issues related to the data platform in a timely manner Adapt and stay agile in high-paced value-add driven environment Provide technical support to junior engineers collaborating on your project Business Knowledge / Technical Skills: Data Structures & Algorithms Experience with database solutions (OLAP and OLTP) Knowledge of web application deployment processes and application architecture Ability to establish and follow SDLC Proficiency in cloud technologies (Azure, AWS, or GCP) and their data-related services Understanding of Horizontal and Vertical scaling Some experience with IAC (Infrastructure as Code), ARM templates, Bicep, Terraform or AWS CloudFormation is a plus Excellent interpersonal and communication skills with the ability to work effectively across all levels of the organization Working knowledge of project management fundamentals, including agile and continuous improvement methodologies Experience with cloud cost optimization Knowledge of modern technology platforms, tools, and techniques (i.e., Cloud, Machine Learning, IoT/IIoT, etc.) Understanding and experience with data security best practices (encryption, tokenization, masking) Basic knowledge of regulatory and compliance policies for data management (CCPA, GDPR, PCI, PII, HIPPA etc.) Error catching and handling in batch and streaming Proficient in one of the following languages: Python, C#, Java, JavaScript Proficient in SQL Experience with warehousing solutions like: Snowflake, BigQuery, Redshift, Synapse Proficiency in effective code management, collaboration and version control: GIT Adequate level of knowledge and experience with some of the following: API, YAML, Kafka, Airflow, JSON, AVRO, Parquet Professional Experience & Education: 7+ years of experience in data engineering STEM, Finance, or Economics degree preferred, Masters degree bonus Relevant certification from Azure, AWS, GCP, IBM Cross industry exposure and experience preferred Other Requirements: Willingness to work in ET time zones if required Comfortable working from various locations including office or at home About Cerberus: Established in 1992, Cerberus Capital Management, L.P., together with its affiliates, is one of the world's leading private investment firms. Through its team of investment and operations professionals, Cerberus specializes in providing both financial resources and operational expertise to help transform undervalued and underperforming companies into industry leaders for long-term success and value creation. Cerberus holds controlling or significant minority interests in companies around the world. The Firm’s proprietary operations team, Cerberus Operations and Advisory Company, LLC (COAC), employs world-class operating executives to support Cerberus’ investment teams in the following areas: sourcing opportunities, conducting highly informed due diligence, taking interim management roles, monitoring the performance of investments and assisting in the planning and implementation of operational improvement initiatives at Cerberus’ portfolio companies. Cerberus Technology Solutions is an operating company and subsidiary of Cerberus Capital Management focused exclusively on leveraging emerging technology, data, and advanced analytics to drive transformations. Our expert technologists work closely with Cerberus investment and operating professionals across our global businesses and platforms on a variety of operating initiatives targeted at improving systems and generating value from data.