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Artmac Soft

Compare

4.5

based on 2 Reviews

11 Artmac Soft Jobs

Databricks Solution Architect (AWS, Pyspark)

Artmac Soft

4.5

based on 2 Reviews

10-20 years

Remote

1 vacancy

Databricks Solution Architect (AWS, Pyspark)

Artmac Soft

posted 4mon ago

Job Role Insights

Flexible timing

Key skills for the job

Data Analytics AWS Computer Networking Information Technology Analytical Chemistry Solution Architecting

+ 3 more

Job Description

Must have 10-20 years of experience as a Data Engineer with a strong focus on AWS cloud services with Databricks and Pyspark.
Extensive hands-on experience with Databricks, AWS, and PySpark.
Proven experience in designing and implementing large-scale data solutions on cloud platforms, particularly AWS.
Strong experience in building and managing data pipelines using tools like PySpark, Apache Spark, and Delta Lake.
Experience in data modeling, ETL/ELT processes, and data warehousing solutions.
Expertise in integrating Databricks with AWS services (e.g., S3, Redshift, Glue, Lambda).
Deep knowledge of PySpark and its application in data processing and transformation.
Experience with other big data technologies (e.g., Hadoop, Kafka, Snowflake).
Familiarity with machine learning and data science workflows.
Proficiency in AWS services including S3, Redshift, Glue, EC2, Lambda, and others.
Strong understanding of cloud security, networking, and cost management.
Experience with CI/CD pipelines and DevOps practices in the context of data engineering.
Lead the architecture, design, and development of scalable data solutions using Databricks on AWS.
Design and implement data pipelines, data lakes, and data warehouses to support complex analytical needs.
Architect solutions that leverage PySpark for large-scale data processing and transformation.
Ensure high performance, scalability, and security of the Databricks environment.
Develop data management strategies for ingestion, storage, processing, and access to large datasets.
Lead the implementation of data governance, security, and compliance best practices.
Optimize data storage and processing workflows to ensure efficiency and cost-effectiveness.
Provide technical leadership and mentorship to data engineering and analytics teams.
Collaborate with cross-functional teams including data scientists, data engineers, and business stakeholders to understand requirements and deliver robust solutions.
Lead the troubleshooting and resolution of complex technical issues related to Databricks and AWS environments.