Senior Data Engineer

1 day ago

Atlanta, Georgia, United States Aptonet Full time $120,000 - $180,000 per year

Senior Data Engineer (Databricks) – Hybrid, Metro Atlanta

Location:
Metro Atlanta, GA (Hybrid – 3 days onsite per week)

Type:
Long-term contract / Full-time opportunity

Overview

We are seeking a
Senior Data Engineer
with strong hands-on experience in
Databricks
and modern data engineering practices. This role is ideal for an engineer who enjoys building, optimizing, and maintaining
scalable data pipelines
that enable analytics, business intelligence, and data-driven decision-making across the organization.

The ideal candidate will be highly proficient in
data modeling, data pipeline orchestration, ETL/ELT design
, and
cloud data engineering
(preferably AWS), with the ability to work cross-functionally with data analysts, data scientists, and application teams.

Key Responsibilities

  • Design & Build Data Pipelines:
    Architect, implement, and maintain scalable end-to-end data pipelines using Databricks, Spark, and related technologies.
  • Data Transformation & Optimization:
    Develop efficient data processing and transformation workflows to support analytics and reporting use cases.
  • Data Integration:
    Integrate diverse data sources including APIs, databases, and cloud storage into unified datasets.
  • Performance Tuning:
    Optimize Spark jobs, queries, and workflows for efficiency, scalability, and cost-effectiveness.
  • Collaboration:
    Work closely with cross-functional teams (data science, analytics, business units) to design and implement data solutions that align with business goals.
  • Data Quality & Validation:
    Implement robust validation, monitoring, and observability processes to ensure data accuracy, completeness, and reliability.
  • Automation & Governance:
    Contribute to data governance, security, and automation initiatives within the data ecosystem.
  • Cloud Environment:
    Leverage AWS services (e.g., S3, Glue, Lambda, Redshift) to build and deploy data solutions in a cloud-native environment.

Qualifications

  • Bachelor's or Master's degree in Computer Science, Information Systems, or related field.
  • 5+ years
    of experience as a
    Data Engineer
    or
    Senior Data Engineer
    in enterprise-scale environments.
  • Strong expertise in
    Databricks
    ,
    Apache Spark
    , and
    PySpark
    for data engineering and analytics.
  • Proficiency with
    Python
    and
    SQL
    for data manipulation, automation, and orchestration.
  • Experience designing and maintaining
    ETL/ELT processes
    and
    data pipelines
    for large datasets.
  • Working knowledge of
    AWS
    (preferred) or other cloud platforms (Azure, GCP).
  • Familiarity with data modeling, schema design, and performance tuning in
    data lake
    or
    data warehouse
    environments.
  • Solid understanding of
    data governance
    ,
    security
    , and
    compliance
    principles.
  • Excellent communication, analytical, and problem-solving skills.
  • Strong teamwork skills with the ability to collaborate across distributed teams.

Nice to Have

  • Experience with tools like
    Fivetran
    ,
    Prophecy
    , or
    Precisely Connect
    .
  • Exposure to
    Delta Lake
    ,
    Airflow
    , or
    dbt
    .
  • Prior work in Agile or DevOps-oriented environments.

Benefits (employee contribution):

  • Health insurance
  • Health savings account
  • Dental insurance
  • Vision insurance
  • Flexible spending accounts
  • Life insurance
  • Retirement plan

All qualified applicants will receive consideration for employment without regard to age, race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.

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