Senior Data Systems Engineer
Job Description
Job Description
We are seeking a highly skilled
Senior Data Engineer
with strong
Quality Assurance (QA)
expertise to join our dynamic team for a confidential client. This hybrid role requires two days of onsite work in
Dallas, TX
, with the remainder remote. The ideal candidate will possess extensive experience in
Python development
,
cloud technologies
(preferably
AWS
), and
data engineering practices
, alongside a proven background in
data testing
and
ETL process automation
.
This is a highly competitive opportunity, offering the chance to work with
cutting-edge cloud technologies
and play a pivotal role in a growing team.
Key Responsibilities:
Automate ETL pipelines
using
Python
to streamline data integration, transformation, and migration processes.
Utilize
AWS cloud technologies
, including
S3, Athena, EMR, Glue, Redshift, Kinesis
, and
SageMaker
, to build robust data infrastructure.
Collaborate with cross-functional teams to ensure data architecture and pipelines are
scalable, efficient, and robust
.
Develop, test, and maintain ETL processes
in both
cloud
and
on-prem environments
using tools such as
AWS Glue, Informatica, Ab Initio
, or
Alteryx
.
Lead
data migration efforts
from on-premise to cloud environments, ensuring
data integrity
and
consistency
.
Perform
data analytics
, integration testing, and
data quality validation
within project timelines and budgets.
Implement
DevOps/DataOps
practices, including
CI/CD pipelines
for data integration and testing workflows.
Write complex
SQL queries
and utilize
Unix/Linux scripting
to manipulate and analyze data effectively.
Support machine learning teams with data preparation and model deployment on platforms such as
SageMaker
or
H2O
.
Apply best practices for
ETL testing strategies
, including the creation and execution of test plans and
automated testing frameworks
.
Mandatory Skills & Qualifications:
11-12+ years
of experience in
data engineering
, with substantial exposure to
cloud technologies
(preferably AWS) and
data quality assurance
.
Proficiency in
Python
for automating ETL processes, data integration, and scripting.
Extensive hands-on experience with
AWS services
such as
S3, Athena, EMR, Glue, Redshift, Kinesis
, and
SageMaker
.
Expertise in
SQL
and
Unix/Linux
for data querying, scripting, and troubleshooting.
Experience in
ETL automation
across cloud and on-prem environments using tools like
AWS Glue, Informatica
,
Ab Initio
, and
Alteryx
.
Proven expertise in
data migration
from on-premise to cloud platforms.
Strong background in
DevOps/DataOps
environments, particularly in developing
CI/CD pipelines
for data engineering.
Skilled in
data modeling
,
data warehousing
, and
data integration
strategies.
Experience in
data analytics
and interpreting data from multiple sources for integration.
Knowledge of
ETL testing strategies
and best practices to ensure data integrity and quality.
Preferred Additional Skills:
Familiarity with
machine learning frameworks
such as
SageMaker
,
Machine Learning Studio
, or
H2O
for predictive models and insights.
Knowledge of
Agile methodologies
and experience working in fast-paced, collaborative environments.
Experience in creating and managing
automated test scripts
and frameworks for ETL processes.
Expertise in managing and troubleshooting
data pipelines
in large-scale distributed environments.
Strong communication skills and ability to work collaboratively with cross-functional teams.
Education:
Bachelor s degree
or higher in
Computer Science
,
Data Engineering
,
Information Technology
, or a related field.
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Position Id:
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