Manager Jobs

About The Position

Requirements

• Good Analytical skills to understand the business requirements and translate them into Technical specifications.
• Good hands-on to AWS Data storage products like AWS S3 and Amazon Redshift.
• Ability to participate in major incident management, production stability, etc. as and when required.
• Good Exposure to code versioning tool GIT, Bitbucket and CI/CD Process and project collaboration platform JIRA.
• Excellent verbal and written communication and should be able to work with all the stakeholders.
• Prior experience on working in Agile project management practices.
• Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.
• 6–10 years of overall IT experience, with strong focus on Data Engineering.
• 4+ years of hands-on experience building data pipelines on cloud platforms.
• Proven experience working as a senior data engineer/ETL expert on complex technical problem statements.
• Excellent communication and leadership skills.
• Proficient on designing, developing and supporting Data pipelines with AWS S3, AWS Redshift, YAML Scripting, Apache Airflow and Shell Scripting.
• Solid AWS Cloud experience, including EC2, S3, IAM, and cloud-based data architectures.
• Proficiency in Python for data engineering and automation.
• Strong SQL skills for data analysis, validation, and performance tuning.
• Experience writing and maintaining Shell scripts for automation and operational support.
• Good understanding of Data Warehousing, Data Lakes, and Data Quality concepts.
• Ability to independently analyze requirements and deliver technical solutions.

Nice To Haves

• Exposure on AWS Cloud Tech Stack for Data Engineering.
• Good to have hands on Databricks and Snowflake.
• Exposure to any financial/asset management domain or sales and marketing would be added advantage.
• Knowledge of networking fundamentals and key management services.
• Exposure to Complete CI/CD Process for Deployment and Releases.
• Good understanding/hands-on of application of AI /ML in data engineering and data quality.

Responsibilities

• Design, develop, and support end-to-end data pipelines using cloud-based platforms such as AWS, Redshift, Databricks, and Snowflake.
• Build scalable data ingestion, transformation, and validation frameworks using Python, SQL, and Shell scripting.
• Develop and optimize data pipelines for performance, reliability, and data quality.
• Partner with product owners, analytics teams, and downstream consumers to translate business requirements into technical solutions.
• Support production stability, incident resolution, and root-cause analysis for data platforms.
• Actively participate in architecture discussions, design reviews, and technical walkthroughs.
• Follow Agile delivery practices, including sprint planning, estimation, and issue tracking using JIRA.
• Ensure compliance with data security, governance, and SDLC standards.
• Continuously identify opportunities to improve efficiency, automation, and platform capability.

Benefits

• retirement savings plan (401K) with company match
• insurance coverage including basic life, medical, dental, vision, long-term disability, and other optional additional coverages
• paid-time off including vacation, sick leave, short term disability, and family care responsibilities
• access to our Employee Assistance Program
• incentive compensation including eligibility for annual performance-based awards
• eligibility for certain tax advantaged savings plans
• inclusive development opportunities
• flexible work-life support
• paid volunteer days
• vibrant employee networks