- 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.
- Positive 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

📌 Data Platform and Support Engineeer (Pune)
🏢 Workday
📍 Pune