Description
Client***Bank is one of the top financial services providers in the nation, recognized and awarded for their customer satisfaction, sustainable profitability, and overall stability and security. Originating in North Carolina, they continue to hold all of their IT in the Raleigh-Durham area and have a great reputation for their technical diversity and excellence. They recently went through a merger with CIT and Silicon Valley Bank, becoming one of the top 20 largest financial services companies in the nation, at over $100 billion in assets, achieving status as a Category 4 Bank.
Project Story: This team within the Enterprise Cyber Security Organization was formed due to the need to create a strategic view on data across all security tools, platforms and domains, allowing the organization to look at the data strategically, deliver metrics, create automation and build necessary data planes for integration/collaboration. They are presently working in a new platform that requires changes architecturally, and they need two Data & Automation Engineers to join their team as they continue to grow this platform. One engineer will be hands on in building data engineering pipelines, the other will be 75% hands on, and 25% focused on architecture. This person will work with other senior architects, and must have enough expertise to help less senior team members, pushback when needed, etc.
Qualifications
• 5+ years of experience in building data engineering pipelines on both on-premise and cloud platforms (Snowflake, Databricks)
• Strong experience coding in Python, PySpark, SQL and building automations.
• Knowledge of Cybersecurity, IT infrastructure and Software concepts.
• Knowledge of IT Asset Management, ITIL, ITSM practices will be a plus.
• 3+ years of experience using data warehousing / data lake techniques in cloud environments.
• 3+ years of developing data visualizations using Tableau, Plotly, Streamlit
• Experience with ELT/ETL tools like dbt, Airflow, Cribl, Glue, FiveTran, AirByte, etc.
• Experience on capturing incremental data changes, streaming data ingestion and stream processing.
• Experience in processes supporting data governance, data structures, metadata management.
• Solid grasp of data and analytics concepts and methodologies including data science, data engineering, and data story-telling
Responsibilities
• Understand business requirements and existing system designs, security applications and guidelines, etc.
• Work with various SME’s in understanding business process flows, functional requirements specifications of existing system, their current challenges and constraints and future expectation.
• Streamline the process of sourcing, organizing data (from a wide variety of data sources using Python, PySpark, SQL, Spark) and accelerating data for analysis.
• Support the data curation process by feeding the data catalog and knowledge bases.
• Create data tools for analytics and data scientist team members that assist them in building and optimizing the data products for consumption.
• Work with data and analytics experts to strive for greater functionality in the data systems.
• Clearly articulate data stories using data science, advanced statistical analysis, visualization tools, PowerPoint presentations, written and oral communication.
• Manage technical, analytical, and business documentation on all data efforts.
• Engage in hands on development and work with both onsite and offsite leads and engineers.
