Global IT Data Engineer Senior Specialist

What You'll Do

• Design, document, and implement data pipelines to feed data models for consumption in Snowflake using dbt and Airflow.
• Ensure data correctness and completeness in engineering pipelines for accurate analytical dashboard insights.
• Monitor and triage technical challenges in critical situations requiring immediate resolution.
• Evaluate technical solutions and develop MVPs or PoCs to support research efforts.
• Engage with external stakeholders to stay updated on data security issues and trends.
• Review and provide feedback on the work of other tech team members to support their growth.
• Implement data performance and security policies in alignment with governance objectives and regulatory requirements.
• Mentor and develop team members to enhance their skills and capabilities.

What You'll Bring

Essential Education
• Bachelor's degree or equivalent combination of education and experience.
• Bachelor's degree in information science, data management, computer science or related field preferred.

Essential Experience & Job Requirements
• 5+ years of IT experience with a major focus on data warehouse/database-related projects
• Must have exposure to technologies such as dbt, Apache Airflow, and Snowflake.
• Experience in other data platforms: Oracle, SQL Server, MDM, etc
• Expertise in writing SQL and database objects - Stored procedures, functions, and views. Hands-on experience in ETL/ELT and data security, SQL performance optimization and job orchestration tools and technologies e.g., dbt, APIs, Apache Airflow, etc.
• Experience in data modeling and relational database design
• Well-versed in applying SCD, CDC, and DQ/DV framework.
• Demonstrate ability to write new code i.e., well-documented and stored in a version control system (we use GitHub & Bitbucket)
• Good to have experience with Cloud Platforms such as AWS, Azure, GCP and Snowflake
• Good to have strong programming/ scripting skills (Python, PowerShell, etc.)
• Good to have familiarity with HR systems such as recruitment workflows, applicant tracking systems (ATS), talent acquisition analytics and HR data structures
• Experience working with agile methodologies (Scrum, Kanban) and Meta Scrum with cross-functional teams (Product Owners, Scrum Master, Architects, and data SMEs)
• Excellent written, and oral communication and presentation skills to present architecture, features, and solution recommendations

Who You'll Work With

• Global functional product portfolio technical leaders (Finance, HR, Marketing, Legal,
  Risk, IT), product owners, functional area teams across levels
• Global Data Product Portfolio Management & teams (Enterprise Data Model, Data
  Catalog, Master Data Management)
• Consulting and internal Data Product Portfolio teams across BCG

Additional info

You have experience in data warehousing, data modeling, and the building of data
engineering pipelines. You are well versed in data engineering methods, such as ETL
and ELT techniques through scripting and/or tooling. You are good at analyzing
performance bottlenecks and providing enhancement recommendations; you have a
passion for customer service and a desire to learn and grow as a professional and a
technologist.

• Strong analytical skills related to working with structured, semi-structured, and
  unstructured datasets.
  • Collaborating with product owners to identify requirements, define desired
  outcomes, and deliver trusted results.
  • Building processes supporting data transformation, data structures, metadata,
  dependency, and workload management.
  • In this role, SQL is heavily focused. An ideal candidate must have hands-on
  experience with SQL database design. Plus, Python.
  • Demonstrably deep understanding of SQL (level: advanced) and analytical data
  warehouses (Snowflake preferred).
  • Demonstrated ability to write new code i.e., well-documented and stored in a
  version control system (we use GitHub & Bitbucket)
  • Extremely talented in applying SCD, CDC, and DQ/DV framework.
  • Familiar with JIRA & Confluence.
  • Must have exposure to technologies such as dbt, Apache airflow, and
  Snowflake.
  • Must have a strong Agile mindset, demonstrating adaptability to changing
  project needs, iterative development, and a proactive approach to problemsolving. Must be comfortable embracing feedback and continuously improving
  processes and products.
  • Desire to continually keep up with advancements in data engineering practices.
  • Knowledge of AWS cloud, and Python is a plus.