Job Title: Senior Data Engineer
Hybrid - 909 E Collins Blvd, Richardson, TX 75081.
Any Visa
Experience Level: 6+ Years
Interview Format: Onsite at the CVS office
Required Test: LIVE CODING / PROBLEM SOLVING
Reference letter required - the reference must directly link the candidate
to a prior company they worked at.
When listing Interview availability, you must list both their Phone/Virtual
IV availability AND their Onsite availability.
Description
This person will be responsible for building new Data Pipelines to extract &
transfer data. There will then be an ML Engineer that will deploy the models
you create.
We are seeking an experienced Senior Data Engineer with a strong background
in Python, SQL, and Azure Cloud technologies. In this role, you will be
responsible for designing, building, and maintaining scalable data pipelines
and infrastructure to support our growing data needs. You will collaborate
closely with data scientists, analysts, and other engineering teams to
ensure data availability, integrity, and performance.
Required:
* 6+ years in advanced SQL
* 6+ years in advanced Python
* Scheduling Tool(s): Apache Airflow or Kubeflow (either will work)
* Azure (preferred), GCP, or AWS advanced Public Cloud Experience
* Proficiency in Python for data manipulation, automation, and scripting.
* Advanced SQL skills for complex query writing, optimization, and database
management.
* Experience with Azure Kubernetes.
* Experience with big data technologies (e.g., Spark, Hadoop) and data lake
architectures.
* Familiarity with CI/CD pipelines, version control (Git), and
containerization (Docker) is a plus.
Key Responsibilities:
* Data Pipeline Development:** Design, develop, and maintain robust
ETL/ELT, curated and feature engineering processes using Python and SQL to
extract, transform, and load data from various sources into our data
platforms.
* Database Management:** Optimize, manage, and monitor SQL databases and
data warehouses, ensuring high performance and efficient data retrieval.
* Data Integration:** Work with both structured and unstructured data
sources to integrate diverse data sets into a unified, accessible format.
* Data Quality and Governance:** Implement data quality checks, validation
procedures, and data governance standards to maintain data accuracy and
consistency.
* Collaboration:** Collaborate with cross-functional teams, including data
scientists, data analysts, software engineers, and product managers, to
define data requirements and deliver solutions that meet business needs.
* Performance Tuning:** Optimize performance of large-scale data processing
systems and databases to ensure efficient data access and usage.
* Documentation:** Create and maintain comprehensive documentation for data
engineering processes, architectures, and pipelines.
* Innovation:** Stay up-to-date with the latest trends and technologies in
data engineering and cloud services, recommending and implementing new tools
and techniques as appropriate.
Education:
* Bachelor's degree in Computer Science, Information Technology,
Engineering, or a related field.