• Architect and build scalable data pipelines, ELT workflows, and streaming systems to enable reliable and efficient data consumption

• Lead data infrastructure strategy for large-scale systems, ensuring scalability, performance, and long-term data growth readiness

• Own and optimize cloud infrastructure, driving reliability, scalability, and cost efficiency

• Design and execute data migration strategies using Python and cloud technologies, ensuring seamless transitions with minimal downtime

• Oversee system monitoring, log analytics, and observability; develop dashboards for proactive performance and issue detection

• Leverage Cloud Computing and DevOps principles to automate deployments from staging to data warehouse environments

• Ensure high availability and performance of production systems through proactive maintenance and continuous optimization

• Collaborate cross-functionally with data teams to deliver high-quality, scalable data solutions using SQL and modern data engineering practices

• Facilitate Agile processes as Scrum Master, driving sprint planning, stand-ups, and retrospectives to improve team velocity and delivery

• Mentor engineers and provide technical leadership, promoting best practices in data engineering and cloud infrastructure

• Designing data pipelines, ELT workflows, and streaming engines to prepare data for consumption by end-users

• Planning data storage for large-scale data handling accounting for data growth & constructing data engineering solutions

• Configure data infrastructure; perform automation & orchestration via puppet & ansible to manage complex tasks

• Utilizing Python and cloud technologies to develop and implement migration plans, ensuring smooth transitions for critical data and systems as well as crafting scalable patterns for efficient data consumption

• Responsible for overseeing infrastructure monitoring, performing log analytics, and spearheading the design of monitoring dashboards

• Demonstrating a robust grasp of Cloud Computing and DevOps principles, to automate the deployment of database models from data staging areas to data warehouses.

• Maintaining the current infrastructure to ensure uninterrupted operations and optimal performance.

• Collaborating alongside data team & contribute SQL code to curate required information & perform data development

• Architecting data pipelines & ELT workflow & streaming engines to prep data for end-user consumption

• Planning data storage for large-scale data handling 2TB/month data growth & constructing data engineering solutions

• Configure data infrastructure; perform automation & orchestration via puppet & ansible to manage complex tasks

• Collaborating alongside data team & contribute SQL code to curate required information & perform data development

• Contributing to data migration to GCP by developing & implementing migration plans using Python & GCP technologies

• Migrating critical data & systems to GCP & crafting scalable patterns for data consumption

• Monitor infrastructure & log analytics. Designed 21 Grafana dashboards & improved operational efficiency by 10%

• Engineered Redpanda streaming integration, processing 10M rows from multiple databases to the central data warehouse

• Strong understanding of Cloud Computing & DevOps concepts, experience using CI/CD pipelines to automate the deployment of database models from data staging areas to data warehouses reducing deployment time by 30%

• Exploring KPIs related to HR & Talent Acquisition Ops. to provide insights via Google Data Studio & Tableau dashboards

• Collaborating with operations team to build data infrastructure and transformation to enable efficient decision making

• Assisting HRIS projects, implement and document the changes made to improve the information systems

• Identifying manual processes maintaining information system to design and implement ways to make them automated

• Designed and executed client building strategies by performing brand research and competitor analysis.

• Performed analysis on the data collected by the marketing channels to get meaningful insights using BI tools.

• Developed the Key Performance Indicators and measured the brand progress with the help of BI techniques.

• Worked closely with the marketing team to design the campaignsfor targeting the right audience to build the brand profiles.

• Evaluated the marketing campaign’s effectiveness by tracking the customer habits and market trends.