ZipRecruiter
Job DescriptionJob Description Senior Data Engineer - (100% Remote)
Fully Remote:
Work from anywhere with flexible hours that fit your lifestyle.
Award-Winning Culture:
Be part of a company recognized for exceptional employee satisfaction, inclusivity, and professional development.
Competitive Compensation:
Generous salary, performance bonuses, and comprehensive benefits package.
Professional Growth:
Access to mentorship programs, certifications, and opportunities to advance your career.
Cutting-Edge Tech:
Work with state-of-the-art tools and technologies on impactful, high-visibility projects.
Key Responsibilities:
Design and implement scalable, efficient data pipelines using
Azure Data Lake ,
Databricks ,
Snowflake , and
Synapse Analytics .
Develop and optimize workflows with
Apache Spark
and
Scala
for batch and streaming data processing.
Build, maintain, and enhance robust ETL/ELT pipelines tailored to big data applications within Azure ecosystems.
Manage and optimize data storage solutions like
Azure Data Lake Storage ,
Snowflake , and
Synapse Analytics
to ensure peak performance and cost-efficiency.
Partner with data scientists, analysts, and business teams to ensure the reliability and availability of data platforms.
Monitor and fine-tune the performance of data platforms in production environments.
Enforce best practices for data governance, security, and compliance in Azure-based data frameworks.
Stay ahead of the curve by researching and integrating new big data technologies to enhance scalability and performance.
Requirements:
Essential Skills and Experience:
A minimum of
5 years
of experience in data engineering or related fields.
At least
3 years
of hands-on expertise in
Apache Spark
using
Scala .
Advanced knowledge of
Azure data services , including
Azure Data Lake ,
Azure Databricks ,
Azure Synapse Analytics , and
Azure Data Factory .
Proficiency with
Snowflake , including schema design, performance optimization, and integration with cloud platforms.
Solid expertise in
cloud-based big data solutions , particularly within the Azure ecosystem.
Strong knowledge of
data modeling ,
ETL/ELT pipelines , and
database concepts .
Experience with streaming platforms such as
Spark Streaming ,
Kafka , or
Event Hubs .
Familiarity with
data lake
and
data warehouse architecture
(e.g.,
Delta Lake ,
Snowflake ,
Synapse ).
Proficiency in DevOps practices, including
CI/CD pipelines
for data engineering workflows.
Skills:
Knowledge of
Python
for data engineering tasks.
Experience with
Azure Machine Learning
or other machine learning platforms integrated with data workflows.
Fully Remote:
Work from anywhere with flexible hours that fit your lifestyle.
Award-Winning Culture:
Be part of a company recognized for exceptional employee satisfaction, inclusivity, and professional development.
Competitive Compensation:
Generous salary, performance bonuses, and comprehensive benefits package.
Professional Growth:
Access to mentorship programs, certifications, and opportunities to advance your career.
Cutting-Edge Tech:
Work with state-of-the-art tools and technologies on impactful, high-visibility projects.
Key Responsibilities:
Design and implement scalable, efficient data pipelines using
Azure Data Lake ,
Databricks ,
Snowflake , and
Synapse Analytics .
Develop and optimize workflows with
Apache Spark
and
Scala
for batch and streaming data processing.
Build, maintain, and enhance robust ETL/ELT pipelines tailored to big data applications within Azure ecosystems.
Manage and optimize data storage solutions like
Azure Data Lake Storage ,
Snowflake , and
Synapse Analytics
to ensure peak performance and cost-efficiency.
Partner with data scientists, analysts, and business teams to ensure the reliability and availability of data platforms.
Monitor and fine-tune the performance of data platforms in production environments.
Enforce best practices for data governance, security, and compliance in Azure-based data frameworks.
Stay ahead of the curve by researching and integrating new big data technologies to enhance scalability and performance.
Requirements:
Essential Skills and Experience:
A minimum of
5 years
of experience in data engineering or related fields.
At least
3 years
of hands-on expertise in
Apache Spark
using
Scala .
Advanced knowledge of
Azure data services , including
Azure Data Lake ,
Azure Databricks ,
Azure Synapse Analytics , and
Azure Data Factory .
Proficiency with
Snowflake , including schema design, performance optimization, and integration with cloud platforms.
Solid expertise in
cloud-based big data solutions , particularly within the Azure ecosystem.
Strong knowledge of
data modeling ,
ETL/ELT pipelines , and
database concepts .
Experience with streaming platforms such as
Spark Streaming ,
Kafka , or
Event Hubs .
Familiarity with
data lake
and
data warehouse architecture
(e.g.,
Delta Lake ,
Snowflake ,
Synapse ).
Proficiency in DevOps practices, including
CI/CD pipelines
for data engineering workflows.
Skills:
Knowledge of
Python
for data engineering tasks.
Experience with
Azure Machine Learning
or other machine learning platforms integrated with data workflows.