Bachelor's degree in information systems, Computer Science, or related field; Master's preferred.
6 to 10 years of experience in data engineering.
Proficiency in SQL and Python.
Experience with data pipeline tools like Apache Airflow, DBT, Snowflake, AWS Glue.
Familiarity with cloud platforms such as AWS, Azure, GCP.
Experience with analytical tools like PowerBI, Looker, and Tableau.
Strong leadership and project management skills.
Responsibilities
Oversee the end-to-end delivery of large-scale data engineering initiatives.
Guide and develop junior engineers through code reviews and knowledge sharing.
Design scalable and secure data architectures in collaboration with architects.
Implement automation for data ingestion, transformation, and deployment.
Proactively monitor data pipelines and resolve technical issues.
Benefits
Medical, Dental, and Vision Insurance
Flexible Spending Account
Health Savings Account
401(k) Plan with Company Match
Company-paid Short-Term and Long-Term Disability
Company-paid Life Insurance
Paid Holidays and Vacation
Employee Referral Program
Employee Assistance Program
Wellness Programs
Paid Community Service Opportunities
Tuition Reimbursement
Ongoing Training & Personal Development
And More!
Full Job Description
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Job Title: Data Engineer (hybrid)
Location: US-GA-Atlanta (Sandy Springs)
FLSA: Exempt
#LI-Hybrid
Job Overview:
The Data Engineer leads complex data engineering projects and drives innovation in data architecture and automation.
Job Responsibilities:
Oversee the end-to-end delivery of large-scale data engineering initiatives.
Guide and develop junior engineers through code reviews and knowledge sharing.
Design scalable and secure data architectures in collaboration with architects.
Implement automation for data ingestion, transformation, and deployment.
Proactively monitor data pipelines and resolve technical issues.
The above statements are intended only to describe the general nature of the job and should not be construed as an all-inclusive list of position responsibilities.
Job Requirements:
Bachelor's degree in information systems, Computer Science, or related field; Master's degree preferred; Equivalent combination of education and experience might be considered.
6 to 10 years of experience in data engineering
Proficiency in SQL and Python.
Experience with data pipeline tools (e.g., Apache Airflow, DBT, Snowflake, AWS Glue).
Familiarity with cloud platforms (AWS, Azure, GCP).
Needs experience with Analytical tools (PowerBI, Looker, and Tableau).
Strong leadership and project management skills.
Advanced knowledge of distributed data processing.
