artechllc.com
Location
Portland, OR (Local or Willing to relocate) Overview
We are seeking a highly skilled
Databricks Data Engineer
with a minimum of 10 years of total experience, including strong expertise in the
retail industry . The ideal candidate will be responsible for designing, developing, and optimizing data pipelines and architectures to support advanced analytics and business intelligence initiatives. This role requires proficiency in
Python, SQL, cloud platforms, and ETL tools
within a retail-focused data ecosystem. Responsibilities
Design, develop, and maintain scalable
data pipelines
using
Databricks and Snowflake . Work with
Python libraries
such as Pandas, NumPy, PySpark, PyOdbc, PyMsSQL, Requests, Boto3, SimpleSalesforce, and JSON for efficient data processing. Optimize and enhance
SQL queries, stored procedures, triggers, and schema designs
for
RDBMS (MSSQL/MySQL) and NoSQL (DynamoDB/MongoDB/Redis)
databases. Develop and manage
REST APIs
to integrate various data sources and applications. Implement
AWS cloud solutions
using AWS Data Exchange, Athena, Cloud Formation, Lambda, S3, IAM, STS, EC2, and EMR. Utilize
ETL tools
such as Apache Airflow, AWS Glue, Azure Data Factory, Talend, and Alteryx to orchestrate and automate data workflows. Work with
Hadoop and Hive
for big data processing and analysis. Collaborate with cross-functional teams to understand business needs and develop
efficient data solutions
that drive decision-making in the
retail domain . Ensure
data quality, governance, and security
across all data assets and pipelines. Required Qualifications
10+ years
of total experience in data engineering and data processing. 6+ years
of hands-on experience in
Python programming , specifically for data processing and analytics. 4+ years
of experience working with
Databricks and Snowflake . 4+ years
of expertise in
SQL development, performance tuning, and RDBMS/NoSQL databases . 4+ years
of experience in designing and managing
REST APIs . 2+ years
of working experience in
AWS data services . 2+ years
of hands-on experience with
ETL tools
like Apache Airflow, AWS Glue, Azure Data Factory, Talend, or Alteryx. 1+ year
experience with
Hadoop and Hive . Strong understanding of
retail industry data needs
and best practices. Excellent problem-solving, analytical, and communication skills. Preferred Qualifications
Experience with
real-time data processing and streaming technologies . Familiarity with
machine learning and AI-driven analytics . Certifications in
Databricks, AWS, or Snowflake . This is an exciting opportunity to work on
cutting-edge data engineering solutions
in a
fast-paced retail environment . If you are passionate about leveraging data to drive business success and innovation, we encourage you to apply! #J-18808-Ljbffr
Portland, OR (Local or Willing to relocate) Overview
We are seeking a highly skilled
Databricks Data Engineer
with a minimum of 10 years of total experience, including strong expertise in the
retail industry . The ideal candidate will be responsible for designing, developing, and optimizing data pipelines and architectures to support advanced analytics and business intelligence initiatives. This role requires proficiency in
Python, SQL, cloud platforms, and ETL tools
within a retail-focused data ecosystem. Responsibilities
Design, develop, and maintain scalable
data pipelines
using
Databricks and Snowflake . Work with
Python libraries
such as Pandas, NumPy, PySpark, PyOdbc, PyMsSQL, Requests, Boto3, SimpleSalesforce, and JSON for efficient data processing. Optimize and enhance
SQL queries, stored procedures, triggers, and schema designs
for
RDBMS (MSSQL/MySQL) and NoSQL (DynamoDB/MongoDB/Redis)
databases. Develop and manage
REST APIs
to integrate various data sources and applications. Implement
AWS cloud solutions
using AWS Data Exchange, Athena, Cloud Formation, Lambda, S3, IAM, STS, EC2, and EMR. Utilize
ETL tools
such as Apache Airflow, AWS Glue, Azure Data Factory, Talend, and Alteryx to orchestrate and automate data workflows. Work with
Hadoop and Hive
for big data processing and analysis. Collaborate with cross-functional teams to understand business needs and develop
efficient data solutions
that drive decision-making in the
retail domain . Ensure
data quality, governance, and security
across all data assets and pipelines. Required Qualifications
10+ years
of total experience in data engineering and data processing. 6+ years
of hands-on experience in
Python programming , specifically for data processing and analytics. 4+ years
of experience working with
Databricks and Snowflake . 4+ years
of expertise in
SQL development, performance tuning, and RDBMS/NoSQL databases . 4+ years
of experience in designing and managing
REST APIs . 2+ years
of working experience in
AWS data services . 2+ years
of hands-on experience with
ETL tools
like Apache Airflow, AWS Glue, Azure Data Factory, Talend, or Alteryx. 1+ year
experience with
Hadoop and Hive . Strong understanding of
retail industry data needs
and best practices. Excellent problem-solving, analytical, and communication skills. Preferred Qualifications
Experience with
real-time data processing and streaming technologies . Familiarity with
machine learning and AI-driven analytics . Certifications in
Databricks, AWS, or Snowflake . This is an exciting opportunity to work on
cutting-edge data engineering solutions
in a
fast-paced retail environment . If you are passionate about leveraging data to drive business success and innovation, we encourage you to apply! #J-18808-Ljbffr