Purple Drive
AWS Data Engineer
Location:
Owings Mills, MD - Hybrid Onsite (LOCAL CANDIDATES ONLY!)
Contract Role
Role Overview
We are seeking a highly skilled
AWS Data Engineer
with extensive experience in designing, developing, and optimizing large-scale data pipelines and cloud-native solutions. The ideal candidate will bring strong expertise in
Python, PySpark, Apache Airflow, and AWS services , with a proven background in data migrations, enterprise data warehouses, and data lakes.
Key Responsibilities
Design, develop, and optimize
data pipelines
using Apache Airflow. Build scalable data solutions across
Operational Data Stores, Data Warehouses, Data Lakes, and Data Marts . Leverage AWS services such as
EKS, EMR, Glue, HashiCorp Vault, Docker, and Kubernetes
for data engineering solutions. Apply strong SQL knowledge to design and manage
data models and warehouse solutions . Collaborate with
business and IT stakeholders
to gather requirements and deliver high-quality solutions. Support data migration initiatives and implement
ETL/ELT pipelines
(DBT/Glue/EMR experience is a plus). Contribute to Agile-based development processes with accurate
effort estimation and planning . Must-Have Skills
8+ years of
hands-on experience
in Python, PySpark, Apache Airflow, and AWS services (EKS, EMR, Glue, Kubernetes, Docker, HashiCorp Vault). 10+ years of overall experience in
data migrations and warehouse development . Strong knowledge of
SQL
and the complete
Data Warehousing lifecycle . Excellent
communication skills
to work across business and technical teams. Proven ability to
plan, estimate, and execute
data engineering projects. Nice-to-Have Skills
Experience with
cloud-native ETL/ELT tools
such as DBT, Glue, or EMR. Prior experience in
Agile environments
with sprint-based delivery.
Location:
Owings Mills, MD - Hybrid Onsite (LOCAL CANDIDATES ONLY!)
Contract Role
Role Overview
We are seeking a highly skilled
AWS Data Engineer
with extensive experience in designing, developing, and optimizing large-scale data pipelines and cloud-native solutions. The ideal candidate will bring strong expertise in
Python, PySpark, Apache Airflow, and AWS services , with a proven background in data migrations, enterprise data warehouses, and data lakes.
Key Responsibilities
Design, develop, and optimize
data pipelines
using Apache Airflow. Build scalable data solutions across
Operational Data Stores, Data Warehouses, Data Lakes, and Data Marts . Leverage AWS services such as
EKS, EMR, Glue, HashiCorp Vault, Docker, and Kubernetes
for data engineering solutions. Apply strong SQL knowledge to design and manage
data models and warehouse solutions . Collaborate with
business and IT stakeholders
to gather requirements and deliver high-quality solutions. Support data migration initiatives and implement
ETL/ELT pipelines
(DBT/Glue/EMR experience is a plus). Contribute to Agile-based development processes with accurate
effort estimation and planning . Must-Have Skills
8+ years of
hands-on experience
in Python, PySpark, Apache Airflow, and AWS services (EKS, EMR, Glue, Kubernetes, Docker, HashiCorp Vault). 10+ years of overall experience in
data migrations and warehouse development . Strong knowledge of
SQL
and the complete
Data Warehousing lifecycle . Excellent
communication skills
to work across business and technical teams. Proven ability to
plan, estimate, and execute
data engineering projects. Nice-to-Have Skills
Experience with
cloud-native ETL/ELT tools
such as DBT, Glue, or EMR. Prior experience in
Agile environments
with sprint-based delivery.