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Artmac Soft

Compare

4.5

based on 2 Reviews

12 Artmac Soft Jobs

Technical Lead (AWS, Pyspark)

Artmac Soft

4.5

based on 2 Reviews

10-20 years

Remote

1 vacancy

Technical Lead (AWS, Pyspark)

Artmac Soft

posted 3mon ago

Job Role Insights

Flexible timing

Key skills for the job

Digital Marketing Medical Coding Python AWS Information Technology Agile Coaching

+ 2 more

Job Description

Must have 10-20 years of experience in software development and data engineering.
Strong experience in building and managing data pipelines using PySpark and other Big Data technologies.
Extensive experience with AWS cloud services, including but not limited to S3, EMR, Lambda, Glue, Redshift, and Athena.
Proficiency in Python programming and experience with data processing frameworks (e.g., Apache Spark, Hadoop).
Strong understanding of data warehousing concepts, ETL processes, and data modeling.
Proven experience in leading and managing technical teams in agile environments.
Experience with CI/CD pipelines, version control systems (e.g., Git), and DevOps practices.
Excellent problem-solving skills, with a focus on scalability and performance optimization.
Strong communication, leadership, and project management skills.
Lead the design, development, and deployment of scalable data processing solutions using AWS services and PySpark.
Oversee the architecture and technical design of data pipelines, ETL processes, and data warehousing solutions.
Manage and mentor a team of data engineers, architects, and developers, providing technical guidance and leadership.
Collaborate with cross-functional teams, including data scientists, analysts, and product managers, to understand data requirements and translate them into technical specifications.
Drive the adoption of best practices in cloud architecture, data engineering, and software development.
Ensure the reliability, performance, and security of data systems in cloud environments.
Develop and maintain documentation, including architecture diagrams, data flow designs, and technical specifications.
Monitor, troubleshoot, and optimize data pipelines and cloud-based applications to ensure high performance and availability.
Lead code reviews, ensure coding standards, and foster a culture of continuous improvement.
Stay up-to-date with industry trends, emerging technologies, and best practices in AWS and data engineering.