Principal Engineering I, Eng Corp

Qualifications:

Bachelor's or Master's degree in Computer Science, Computer Engineering, or equivalent field

5+ years of experience in data engineering and database management

Expertise in SQL to explore and manipulate huge datasets and DBT for data transformation and pipeline development

Experience with relational databases (e.g., PostgreSQL, MySQL, MS-SQL)

Experience with data warehouse/data lake technologies (e.g., Snowflake, Redshift, Bigquery, Databricks)

Strong knowledge in Snowflake architecture and concepts

Strong working experience in Snowflake using warehouses, stored procedures, streams, snow pipes, tasks, stages, storage integration, ingestion frameworks and tools etc

Ability to develop ELT/ETL pipelines to move data to and from Snowflake data store using combination of Python and Snowflake SnowSQL

Strong hands-on experience with requirements gathering analysis, coding, testing, implementation, maintenance, and review

Extensive development experience using Python and other scripting languages (Perl, shell etc.) and OOPs concepts

Experience in working with AWS, MS Azure, or other cloud providers

Experience with AWS services such as Lambda or S3, AWS Certification

Good hands-on experience on scheduling tools such as Airflow, Control M, Autosys scheduling tools

Good hands-on experience with PL/SQL Oracle programming. (Writing sql queries, stored procedure, functions, triggers etc.)

Solid experience with application Support & resolving production issues

Possessing outstanding technical and analytical skills with strong business knowledge

Experience in Agile methodologies (Kanban and SCRUM), communication, and interpersonal skills

Experience with data visualization tools like Power BI, Tableau.

Experience on power platform is a plus

Responsibilities

Develop and test scalable automated architectures that enable data extraction and transformation for predictive or prescriptive modeling

Design and build data pipelines, architectures, and data structures that allow for the efficient flow of data from various sources into our data warehouses

Develop and implement data models, data mapping, and visualization techniques to help stakeholders understand and analyze complex data sets

Develop and maintain data dictionaries, data lineage, and data governance policies to improve our understanding of the data we work with

Collaborate with other internal teams to identify key data needs and automate data processing and analysis wherever possible

Stay up-to-date with emerging technologies, trends, and best practices in data engineering and continuously improve our data infrastructure and processes

Write and maintain ETL (Extract, Transform, Load) scripts and workflows

Create data visualizations, reports, and dashboards that provide insights to stakeholders

Primary Skill Sets - Snowflake and Data Engineer, AWS Cloud.