Data Engineer
1 month ago
POSITION DESCRIPTION :
WHAT YOU'LL DO :
- Architect, Design, document & implement the data pipelines to feed data models for subsequent consumption in Snowflake using dbt, airflow.
- Ensure correctness and completeness of the data being transformed via engineering pipelines for end consumption in Analytical Dashboards.
- Actively monitor and triage technical challenges in critical situations that require immediate resolution.
- Evaluate viable technical solutions and share MVPS or PoCs in support of the research
- Develop relationships with external stakeholders to maintain awareness of data and security issues and trends.
- Review work from other tech team members and provide feedback for growth Implement Data Performance, Data security policies that align with governance objectives and regulatory requirements
YOU'RE GOOD AT :
- 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 in 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 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. UDA 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.Desire to continually keep up with advancements in data engineering practices. Knowledge on AWS cloud, Python is a plus.
YOU BRING (EXPERIENCE & QUALIFICATIONS) :
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 major focus on data warehouse/database related projects
- Must have exposure to technologies such as dbt, Apache Airflow, Snowflake.
- Experience in data platforms: Snowflake, Oracle, SQL Server, MDM etc.
- Expertise in writing SQL and database objects - Stored procedures, functions, views. Hands on experience in ETL/ELT and data security, SQL performance optimization and job orchestration tools and technologies e.g., dbt, Attunity, Golden Gate, 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 know about developing financial models and forecasting to support financial planning and decision-making processes.
- Experience around responsibility for analyzing and interpreting financial data to provide valuable insights and support strategic decision-making.
- Experience working with agile methodologies (Scrum, Kanban) and Meta Scrum with cross-functional teams (Product Owners, Scrum Master, Architects, and data SMEs).
- Excellent written, oral communication and presentation skills to present architecture, features, and solution recommendations
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