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Specialist I - Software Engineering (Technical Lead - Python, Databricks, AWS)

7 - 11 years

0 Lacs

karnataka

Posted:2 days ago| Platform: Shine logo

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Skills Required

python aws databricks cicd pipelines

Work Mode

On-site

Job Type

Full Time

Job Description

As a Technical Lead in Data Engineering specializing in Python and Databricks, you will play a crucial role in leading the design, development, and support of data pipelines and analytics solutions. Your responsibilities will include architecting scalable and secure cloud-based data platforms, collaborating with cross-functional teams to understand requirements, and mentoring a team of engineers to foster technical excellence and continuous improvement. You will be expected to ensure best practices in coding, testing, and deployment, manage project timelines and stakeholder expectations, and integrate and optimize data workflows with Databricks and other platforms. Additionally, you will conduct code reviews, provide technical leadership in sprint planning and retrospectives, and have a strong focus on delivering high-quality solutions. To excel in this role, you should possess at least 7 years of experience in software/data engineering, with a strong proficiency in Python for data processing and automation. Hands-on experience with Databricks, including Spark, Delta Lake, and notebooks, is essential. A deep understanding of AWS services such as S3, Lambda, Glue, EC2, and IAM is also required. Experience with CI/CD pipelines, version control (Git), and infrastructure as code is crucial, along with a background of working in an Agile/Scrum environment. Proven experience in leading technical teams, excellent communication skills, and stakeholder management are key aspects of this role. While not mandatory, it would be beneficial to have AWS certification (e.g., Solutions Architect, Data Analytics), familiarity with Snowflake for data warehousing and analytics, and knowledge of data governance, security, and compliance. Your expertise in Python, AWS, Databricks, and CI/CD pipelines will be instrumental in driving the success of data engineering projects.,

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