Data Engineer

Job Title: Data Engineer

Location: Seattle, WA (Hybrid)

Client: Starbucks

Need the consultant to be at Starbucks 3 days a week.

Job Description 1 : Sr Backend developer/ data engineer (Azure Databricks using Python/Pyspark and Power BI Development)

Key Responsibilities:

Develop and optimize ETL pipelines using Python/PySpark and Databricks.

Work with large-scale datasets and build distributed computing solutions.

Design and implement data ingestion, transformation, and processing workflows.

Write efficient and scalable Python code for data processing.

Collaborate with data engineers, data scientists, and business teams to deliver insights.

Optimize performance and cost efficiency for big data solutions.

Implement best practices for CI/CD, testing, and automation in a cloud environment.

Monitor job performance, troubleshoot failures, and fine tune queries.

Build automated reports and dashboards with the help of Power BI and other reporting tools.

Understand business requirements to set functional specifications for reporting applications.

Be experienced in tools and systems on MS SQL Server BI Stack, including SSRS and TSQL, Power Query, PowerBI, and DAX.

Be able to quickly shape data into reporting and analytics solutions.

Have knowledge of database fundamentals such as multidimensional database design, relational database design, and more.

Required Skills & Qualifications:

Strong hands-on experience with Apache Spark (PySpark) for data transformation.

Experience working with Databricks for data processing and analytics.

Good knowledge of SQL and NoSQL databases.

Experience with Cloud platforms (Azure, AWS, or Google Cloud Platform) and storage solutions.

Familiarity with CI/CD pipelines, DevOps practices, and automation tools.

Understanding of data lake, data warehouse, and data modeling concepts.

Knowledge of job orchestration tools like Airflow, Azure Data Factory, or AWS Glue.

Strong problem-solving and debugging skills in distributed environments.

Create data-rich dashboards, implementing Row-level Security (RLS) in Power BI, writing DAX expressions.

A minimum experience of two to three years working with BI tools or any data-specific role with a sound knowledge of database management, data modeling, business intelligence, SQL querying, data warehousing, and online analytical processing (OLAP).

In-depth understanding and experience with Microsoft BI stacks such as Power Pivot, SSIS, SSRS, and SSAS.

The ability to drill down on data and visualize it in the best possible way through charts, reports, or dashboards.

Understanding of software development architecture and technical aspects.