Senior Data Engineer - Cloud and ETL Pipelines
This role involves designing and maintaining data systems and pipelines supporting large-scale data initiatives for Verizon. The candidate will collaborate with cross-functional teams to develop scalable data solutions and optimize workflows. It offers a remote work environment with potential for full-time conversion after 6 months.
Key Highlights
Technical Skills Required
Benefits & Perks
Job Description
+1 571-556-1002 |[email protected]
Hiring Data Engineer -W2|| 100% Remote
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Please check the JD and share your updated resume
JD
Data Engineer-W2
Location: Remote (Strong preference for candidates based in Atlanta, Dallas, or Miami)
Start Date: ASAP
Duration: 12 Months, with eligibility for full-time conversion at 6 months
About the Role
We’re looking for a Data Engineer to join a multidisciplinary Agile team supporting large-scale data initiatives for Verizon. This role focuses on designing, building, and maintaining the data systems and pipelines that enable advanced analytics and data-driven decision-making across the organization.
What You’ll Do
Partner with software engineers, business stakeholders, and subject matter experts to translate requirements into scalable data solutions.
Develop, implement, and deploy ETL pipelines and workflows.
Preprocess and analyze large datasets to uncover meaningful insights.
Validate, refine, and optimize data models for performance and reliability.
Monitor and maintain data pipelines in production, identifying improvements and refining workflows.
Document development processes, workflows, and best practices to support team knowledge sharing.
What We’re Looking For
Education & Experience
Master’s degree in Computer Science, Engineering, Statistics, or a related field
OR
Associate-level Azure certifications paired with strong hands-on experience.
Minimum of 4 years of Data Engineering experience, ideally within large or enterprise environments.
Technical Skills
Strong programming proficiency in Python, PySpark, and SQL.
Experience building and optimizing ETL workflows using tools such as Spark, Snowflake, Airflow, Azure Data Factory, AWS Glue, or Redshift.
Ability to craft and optimize complex SQL queries and stored procedures.
Experience developing and maintaining scalable, high-performing data models.
Hands-on expertise with Snowflake, including Snowpark for data processing.
Exposure to API integrations to support data workflows.
Experience implementing CI/CD pipelines through DevOps platforms.
Solid understanding of Azure cloud infrastructure and services.
Ideal Candidate Profile
Strong ETL developer with hands-on Snowflake + PySpark experience.
Skilled in building production-grade, scalable data pipelines.
Comfortable collaborating across technical and business teams in an Agile environment.
Detail-oriented with strong documentation and communication skills.
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