Testimonials

  • Pinned
    The career guidance session was insightful and well-structured. Seshendranath provided clear, personalized advice tailored to my goals, helping me identify strengths, skill gaps.
    Tom
  • Pinned
    Our session was highly productive and insightful, offering clear solutions to the challenges we discussed. The collaborative atmosphere made it easy to align on our next steps and move forward with confidence.
    Ramky
  • Pinned
    The Data Engineering Architecture Review session provided valuable insights into current system design, highlighting strengths in scalability and data flow efficiency. The collaborative discussion helped identify optimization opportunities for cost efficiency and data governance improvements.
    Ramky
  • Pinned
    The Databricks Compute Cost Savings Review showcased effective strategies to optimize compute performance while cutting costs, emphasizing cluster efficiency, workload tuning, and automation to achieve significant savings.
    Anonymous
  • Pinned
    The Cloud Compute Cost Savings session provided valuable insights into optimizing cloud infrastructure spend. The practical examples and strategic approaches to reducing AWS OPEX were especially impactful.
    Anonymous
  • Pinned
    The Cloud Compute Cost Savings Review session by Seshendranath , was extremely insightful and practical. It offered clear strategies for optimizing cloud spend without compromising performance. Truly a valuable session for anyone managing cloud resources!
    Lakshmi

Services

Video meeting . 60 mins
5

Optimizing spark jobs and understanding internals

Use spark resources to the fullest
FREE
Video meeting . 30 mins
5
FREE
Video meeting . 60 mins

Building Enterprise-Scale Data Products

Building Data Products the right way
FREE
Video meeting . 60 mins
4.5
FREE
Video meeting . 60 mins
5
FREE
Video meeting . 60 mins
FREE
Video meeting . 60 mins
4.7
FREE
Video meeting . 60 mins
5

Data engineering Architecture Review

Optimize the data pipelines
FREE

Ratings and feedback

4.8/5
16 ratings
16
Testimonials
5/5
The RAG-Powered LLM session was fantastic! I loved how the concepts were broken down with clarity and real-world relevance. It was great to see how RAG empowers LLMs to deliver accurate, up-to-date, and context-aware responses. Thanks to the organizers and speaker for such an enlightening and motivating session!

About me

Dynamic and results-driven versatile Senior Data Engineering Leader with over 15+ years of expertise in designing and implementing advanced data solutions. Proven track record in leading teams and managing large-scale data engineering projects. Expert in optimizing data pipelines, migrating legacy systems to modern technologies, and leveraging performance-enhancing techniques. Adept at driving strategic initiatives, ensuring data quality, and delivering actionable insights to support business objectives. Skilled in stakeholder management, cross-functional collaboration, and aligning data strategies with organizational goals. Committed to fostering innovation and excellence in data engineering practices. AREA OF EXPERTISE • Data Architecture & Strategy • ML Engineering/ MlOps • Team Leadership & Mentorship • Agile & DevOps Methodologies • Data Governance & Compliance • Stakeholder Management & Communication • Building Data Lakes, Data Fabric. • Product Planning and OKR Definition. • Leading MVP Definition and Development. • Strategic Annual and Quarterly Planning. • Project and Resource Planning. • Optimization and simulation. • Cross-functional team management. • Data security, privacy, and Governance. • Tactical Execution/ Project Oversight. • Quantitative analysis TECHNICAL SKILLS • ML Engineering: MLflow, Kubeflow, Feature Store, Unity catalog, Model Registry. • Hadoop & Spark Stack: Hadoop Ecosystem, Spark 2.x, Datafram API, Spark SQL, Databricks and Map Reduce, Alluxio. • Streaming Stack: Spark Structure Streaming, Kafka, Kinesis, MSK, Flume. • Database Technologies: Teradata, Oracle, Hive, Athena, Presto. • Cloud: AWS, EKS, EC2, S3, Glue, EMR, Lambda, CloudWatch, SNS, SQS, EKS. • No SQL: HBase, DynamoDB • Languages: Scala, Python and Shell • Monitoring and Reporting: Kubernetes, Airflow, Tableau, Looker and UC4 • Formats: Parquet, Delta, Iceberg. • CI/CD: GIT, Jenkins, Nexus, Seldon Core. • Security & Privacy: Privacera, Kerberos, Ranger, Audits, CPPA & GDPR data privacy.