We are looking for an experienced Data Engineer to join our growing team at ProCogia. As a Data Engineer, you should have the expertise in the design, creation, management, and business use of extremely large data sets. You know and love working with analytic tools, can write excellent SQL, and ETL code (e.g. SSIS, Informatica, etc.), and can use your technical skills and creative approaches to help clients solve their most critical business challenges. This individual will be an integral part of Data Solutions being provided. In addition to working with clients, collaborate closely with members of the team who are focused on advanced analytics, data science, business stakeholders and program management.
Design, construct, test, optimize, and deploy solutions.
Deliver transformative solutions to clients that are aligned to industry best practices and provide thought leadership in data architecture and engineering space.
Exceptional analytical, conceptual, and problem-solving abilities.
Experience with both on-prem and cloud data architecture.
Strong focus on back end data integration.
Strong focus on the design and development of data warehouses.
Highly self-motivated to deliver both independently and with strong team collaboration.
Ability to creatively take on new challenges and work outside comfort zone.
Strong written and oral communications along with presentation and interpersonal skills.
Conduct and support white-boarding sessions, workshops, design sessions, and project meetings as needed, playing a key role in client relations.
Strong aptitude for learning new technologies and analytics techniques.
Required Skills and Experience:
Quantitative background with 3+ years of experience applying data architecture or engineering to solve real-world business problems.
Preferred Skills and Experience:
Relational and dimensional database structures, theories, principles, and practices.
Manipulating / mining data from database tables (SQL Server, Redshift, Oracle).
SQL, ETL / ELT optimization, and analytics tools including R, HiveQL, and Python.
Distributed processing on Hadoop or Spark.
Solution architecture on cloud platforms such as AWS, Azure, and GCP.
Bachelor’s degree in a technical field (computer science, applied mathematics, statistics, etc.).
Practical knowledge of data visualization tools (e.g., Tableau, Power BI) a plus.