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The Data Engineer will discover and analyze data and write data pipelines using ELT patterns to support data munging, data preparation and reporting needs. They will help analyze product data and might support with building Power BI and/or Sisense reports; as well as help with general data team duties (performing QA and audits, running loads, generating memo files, ad hoc data requests).

Responsibilities include:

• Design, build, and maintain scalable data pipelines to support data ingestion and transformations into intermediate and final data targets;
• Maintain (and build from scratch if missing) documentation of data architecture, processes, and workflows;
• Participate in the data modeling of data targets in Snowflake, designed for querying by reporting tools (Power BI and Sisense) and data-savvy personnel;
• Integrate data from databases, APIs, and third-party platforms to facilitate data flow;
• Recognize and adopt best practices in reporting and analysis: data integrity, test design, analysis, validation, and documentation;
• Contribute to the design, development, and maintenance of data ongoing metrics, reports, analyses, dashboards, etc. to drive key business decisions;
• Continually improve ongoing reporting and analysis processes, automating or simplifying self-service support for customers;
• Manage cloud-based resources, drive ongoing query optimization;
• Interface with both internal and external business customers and stakeholders, gathering requirements and delivering complete reporting solutions;

Education:

• Bachelor’s Degree in Computer Science, Mathematics, Statistics, Finance, Information systems or equivalent related technical field experience

Experience:

• 5+ years of professional experience in data analytics, reports development, business analysis or comparable consumer analytics position
• Experience working with advanced SQL and large datasets
• Experience working with Snowflake and dbt
• Experience with tools like Looker, PowerBI, Tableau, R, Domo
• Experience developing customer personalization solutions

Tools & Skills:

• Deep understanding of complex SQL including Joins, Unions, CTEs, Aggregations, Groupings, Lag and Lead, and other advanced concepts.
• Strong understanding Snowflake objects and Snowflake SQL syntax to ensure the right structures are used at the right time for the right purpose; this includes Tables, Views, Functions, Procs, Time Travel, CDC and Streams, Cloning, Primary / Secondary roles, etc.
• Good understanding of DataBricks (ADB preferred) and Azure Data Factory (ADF) to be able to interpret existing solutions;
• Excellent understanding of dbt for our planned (targeted) tool for a migration project;
• Good understanding of reporting tools, preferably PowerBI and/or Sisense;

Key Competencies:

• Proven problem-solving skills and attention to detail
• Ability to work with business owners to define key business questions and build data sets that answer those questions
• Ability to deal with ambiguity and competing objectives in a fast-paced environment
• Excellent verbal/written communication and data presentation skills, including an ability to effectively communicate with both business and technical teams
• Effective in a small, multi-disciplined, fast-paced team environment.
• Have ability to consistently deliver results with quick turnaround. Strong spirit of innovation, self-starter, independent, and with ability to come up with solutions to meet business problems.
• Advanced working knowledge of data mining using SQL, Python, ETL, and Excel
• Experience in developing new or improving data engineering capabilities to facilitate deeper analysis and reporting
• Experience in proactive data quality and monitoring to ensure accurate datasets
• Experience in working with numerous data formats including querying JSON stored records
• Understanding of data warehousing and data modeling

Assets:

• Experience in Telecom or banking industry, particularly in the collection or retention space
• Experience with performing data transformations with Azure Data Factory to feed custom reporting models
• Experience in scripting languages like Python, Perl, Shell script
• Knowledge or experience with performing data transformations with tools like DBT