DBT Data Engineer

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 modelling, 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 ie, 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

Bachelors degree or equivalent combination of education and experience.

Bachelors degree in information science, data management, computer scienc or related field preferred.

Essential Experience Job Requirements

4+ 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 eg, dbt, Attunity, Golden Gate, APIs, Apache Airflow etc

Experience in data modelling and relational database design

Well versed in applying SCD, CDC and DQ/DV framework

Demonstrate ability to write new code ie, 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 knowledge around 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

YOU LL WORK WITH

o Global functional product portfolio technical leaders (Finance, HR, Marketing, Legal,

Risk, IT), product owners, functional area teams across levels

o Global Data Product Portfolio Management teams (Enterprise Data Model, Data Catalog, Master Data Management)

o Consulting and internal Data Product Portfolio teams across BCG

Full time