Data Platform and Support Engineeer

• Monitor the health and performance of data systems, including databases, data warehouses, and data lakes.
• Conduct root cause analysis and implement corrective actions to prevent recurrence of issues.
• Manage and optimize data infrastructure components such as servers, storage systems, and cloud services.
• Develop and implement data quality checks, validation rules, and data cleansing procedures.
• Implement security controls and compliance measures to protect sensitive data and ensure regulatory compliance.
• Design and implement data backup and recovery strategies to safeguard data against loss or corruption.
• Optimize the performance of data systems and processes by tuning queries, optimizing storage, and improving ETL pipeline efficiency.
• Maintain comprehensive documentation, runbooks, and fix guides for data systems and processes.
• Collaborate with multi-functional teams, including data engineers, data scientists, business analysts, and IT operations.
• Lead or participate in data-related projects, such as system migrations, upgrades, or expansions.
• Deliver training and mentorship to junior team members, sharing knowledge and standard methodologies to support their professional development.
• Participate in rotational shifts,including on-call rotations and coverage during weekends and holidays as required,to provide 24/7 support for data systems,responding to and resolving data-related incidents in a timely manner
• Hands-on experience with source version control, continuous integration and experience with release/organizational change delivery tools.

About You

Basic Qualifications:

• 6+ years of experience designing and building scalable and robust data pipelines to enable data-driven decisions for the business.
• BE/Masters in computer science or equivalent is required

Other Qualifications:

• Prior experience with CRM systems (e.g. Salesforce) is desirable
• Experience building analytical solutions to Sales and Marketing teams.
• Experience with very large-scale data warehouse and data engineering projects.
• Experience developing low latency data processing solutions like AWS Kinesis, Kafka, Spark Stream processing.
• Should be proficient in writing advanced SQLs, Expertise in performance tuning of SQLs
• Experience working with AWS data technologies like S3, EMR, Lambda, DynamoDB, Redshift etc.
• Solid experience in one or more programming languages for processing of large data sets, such as Python, Scala.
• Good to have experience working on Snowflake , Fivetran DBT and Airflow
• Ability to create data models, STAR schemas for data consuming.
• Extensive experience in troubleshooting data issues, analyzing end to end data pipelines and working with users in resolving issues