🧳 My Timeline

Taking a much needed break after a decade of building tech and teams at high intensity

After a decade of leading high-performing tech teams and building products at scale, chose to take a short break to recharge and reflect. Managing large teams gave me rich experiences but also made me realize the importance of sustainable growth, deep work, and staying rooted in hands-on problem solving.

• Targets during this break:
  • 👥 Spend more time with family and dogs 🐶
  • 📖 Read more books (Will be sharing some book reviews soon)
  • ✍️ Write more (Substack / Blogs)
  • 🤖 Spend more time with AI
  • 🧑‍💻 Vibe Code? (Why not)
  • 📚 Learn some new stuff
  • 🤔 Think more
  • 💤 Rest more
  • 🥱 Get bored
  • 🔎 Lookout for the next role (Yes, I am actively exploring ‼️)
• If you want to follow what I am doing during this break, checkout this series: https://manikantprasad.com/category/career-learnings/career-break/
• Read about my reflections from a decade of working in and building high-performing teams: https://manikantprasad.com/scale-leadership-framework/ (Work in Progress)

Journey of Pivoting a Data Catalog tool into a visionary in the Data Governance Stack

• Joined the Data & AI Governance charter to help pivot the product into a leader in the space
• Led the development of modules like Governance Workflows, Policy & Compliance, and Data Products from 0 -> 1, contributing to engineering as well as product leadership
• Worked closely with customers to ensure adoption of the capabilities
• Also owned several other existing modules in the product (Authentication, Authorization, Metastore, Admin Management, and Glossary)
• Led a team of 24 cross-functional engineers during this phase of the journey
• Ensured developer productivity by making developers more AI-native
• Outcomes:
  • Atlan Named a Visionary (Q3 2024) and subsequently a Leader in The Forrester Wave™ Data Governance Solutions, Q3 2025
  • More importantly, in the same Forrester Wave report (2025), Atlan also emerged as a Customer Favourite based on all reviews
  • A Visionary in the Gartner^® Magic Quadrant™ for D&A Governance.

Removing entry blockers for accelerating early growth and expansion to the Enterprise world (while building a talent-dense team)

• Joined as the second-ever Engineering Manager, responsible for setting up the engineering culture and rhythm
• Led a team of 22 cross-functional engineers
• Owned two product modules:
  • Connector ecosystem
  • Insights: a governed SQL workbench
• Also started the Customer Engineering practice from 0 -> 1 (Backline Support team)
• For Connectors:
  • Streamlined the assembly line for building connectors to accelerate breadth expansion
  • Built close to 40 new connectors during my tenure
  • Increased depth of integration with existing connectors
• For Insights:
  • The product applies Atlan policies on all queries from the users before sending them to the source, rewriting them for compliance
  • The biggest problem was the reliability of the product, as we faced many query failures after rewrites
  • Dived into all failure patterns to reduce the daily query error rates from 5% to 0.5%
  • The product was put on maintenance after achieving significant reliability, and continued to be a popular offering
• Mentored the Tech Lead and helped them progress into a managerial role for the team
• Created an opportunity for me to take up a new charter within the company

Helping a data-intensive business bring transparency and remove internal viscosity

• Joined the team as their first data hire
• The team had significant data reporting needs to customers, regulatory bodies, and investors.
• The ad-hoc nature of reporting led to a last-minute sprint to get the “right” data and inconsistencies across reporting
• Problems to solve when I joined:
  • Theoretical North stars and current numbers were not known
  • Account teams needed per-customer data every month and quarter for MBRs and QBRs
  • Quarterly investor numbers were often incorrect/inconsistent
  • Leaders often lacked the right data to back their decisions
  • Insurance Partners often came back with data different from internal numbers and took significant effort to find errors and gaps
• Approach:
  • Month 1:
    • Collaborated with Leaders across the organisation to understand their pain points and needs for better operations
    • Engaged with Engineering teams to figure out the latest data models (use of NoSQL in production meant no one knew what the actual data model was)
  • Month 2:
    • Translated organisational requirements into scalable and reusable data models
    • Engaged with vendors to find the right data stack solutions
    • Helped the engineering team better consolidate their data models across the codebase and teams
  • Month 3:
    • Stack finalised (mostly low/no code for speed of execution) and integrated
    • Stack:
      • Data was moved from FirestoreDB to BigQuery using plugins only reliable solution, but it dumped JSON records
      • Hevo: To move data from BigQuery to Snowflake – mostly due to BigQuery’s limitation to interact with nested JSON fields
      • Snowflake: Hevo transformations were used to flatten the JSON imports into wide Snowflake tables
      • dbt: Models to operate on raw dumps to produce clean fact and dimension tables. And subsequently producing wide analytics tables to power analytical views and metrics
      • Metabase: To create data serviceability on top of Snowflake and enable teams to create reports as needed.
  • Month 4:
    • Models completed and North Star dashboards created
    • Led to a massive 20% correction to ad-hoc numbers reported earlier (mostly due to data quality issues that were previously unknown)
  • Month 5 & 6:
    • Enabled internal teams to leverage analytics tables and use Metabase to create internal reports
    • New Claims and other operational dashboards that helped track operational efficiency
• The team struggled with core engineering and business. Data requirements reached stability. No further growth opportunities, and hence decided to move on.

Learning the basics of people management and growing a lean but multi-dimensional team, all while continuing to grow a sustainable product engineering practice

• Got promoted to an Engineering Management role after building the team in India for three years – clueless at this moment how to measure success in this new role
• Learned the art of servant leadership from a couple of excellent mentors within the company
• Continued technical expansion during this time, building an internal Cloud Analytics Platform (leveraging ADLS, Databricks and Snowflake), securing 2 internal and one external security reviews, along with CIO approval for processing PII (Personally Identifiable Information)
  • This helped us migrate all on-prem data pipelines and processing onto the cloud
• Longevity of our engineering practices helped us acquire our only significant competitor in December 2021
• Mentorship success includes:
  • Maintained a 100% retention rate during the tenure while continuing to grow the team (when the industry saw great attrition everywhere)
  • Helping grow the tech lead into the next manager for the team after my exit
  • Mentored an early Actuarial Data Analyst into a Team lead position – ultimately leading a team of 7 other analysts

Learning to execute as a founding engineer while helping navigate a non-engineering team into building products and a subscription-based business

• Joined the Life & Annuity Predictive Analytics (LAPA) team at Milliman as their first Engineering IC (Individual Contributor) and first team member in India
• The team was pivoting from a research practice into a product development organisation to streamline their revenue and operations
• While I joined as a Data Engineer, I worked across functions to lay the ground for iterating on product ideas at a rapid pace
• During my time, I got to work on:
  • Data Engineering (R, Python, Snowflake, Databricks, MariaDB ColumnStore, ADF, Azure Synapse and more)
    • Also ended up writing a cookbook on implementing MariaDB Columnstore with R
  • Cloud Engineering (Azure, Ansible, a little bit of AWS)
  • Quality (Selenium-based browser automation using PyTest)
  • Security (leading security reviews, internal and external, also securing a
    CompTIA Security+ certification on the way. Also leading the SOC II Type II compliance effort)
  • Analytics (Hired Actuarial Data Analysts and helped them become pro at R Shiny to build apps and PySpark to own pipelines on Databricks)
  • DevSecOps (Building CI/CD pipelines in Azure DevOps, implementing security scans via Qualys, and integrating security right into the platform)
• All this while I continued to hire across functions (often without a recruiter) and built the team from the ground up

Databases, SQL, Spark, Scala, Java, and more. Doing it ALL. Learning the art of execution with high agency in a Data team.

• Joined the Data Warehousing and Platform team as a top preference, mostly for the love of numbers
• Started with building Java-based ETL and orchestration frameworks purpose-built to migrate legacy Pentaho pipelines into config-driven jobs
  • This helped reduce the turnaround time for any new file-based ETL requests from days to hours
  • Also, helped standardise requirement gathering and daily stakeholder reporting across all processes and centralised failure monitoring across pipelines
• Various other big or small data projects leveraging VerticaDB and SQL
• Participated in on-call rotations, taking care of nightly loads and other faults/failures
• As the organisation pivoted towards building an in-house data platform, I worked on re-creating popular analytical tables on VerticaDB onto the new platform, leveraging Spark and Scala
• Overall, it was a great learning experience and helped me become a radical owner, self-starter, and learn stakeholder management

The first few experiences of navigating the unknowns and looking deeper

• Early deep dive into Cryptography in college helped me secure my first (and then second) summer internship at ISI Kolkata with Cryptology and Security Research Unit
• Both internships were guided by Prof. Sushmita Ruj
• Projects:
  • 2013: Fine-Grained Privacy Preserving Profile Matching in Proximity-based Mobile Social Network
    • Focused on homomorphic encryption to achieve calculations/scoring while preserving privacy
  • 2014: Malware Propagation Dynamics in Interdependent Networks
    • Focused on studying the spread of different kinds of epidemics between interconnected graphs
    • Mostly to understand the impact of viruses in the Smart Grid or other such networks

Coding, Service, Ownership, Leadership, and more

• Learned programming for the first time
• Joined two college clubs that shaped my four years of journey and beyond:
  • The official coding club, SPAWN
    • Started first year attending classes, helping with operations, and organising events
    • Became the second-ever President of the Club in the 4th Semester
    • Started with taking classes on C, C++, and many other topics from the 4th semester onwards
    • Started “Codex” – an inter-college coding competition in collaboration with HackerRank
    • Year-long event and budget planning
  • The social service club AASRA
    • Spent the first year teaching kids in a nearby orphanage, visiting twice in a week (mostly teaching Maths and English)
    • Took up responsibility as vice-captain of the workplace and managed daily rotations for visits (3rd and 4th semesters)
    • Continued with regular visits throughout the time in college and actively contributed to many events organized by the club for kids or on campus
• Worked under a college professor to research Cryptography and number theory from the 4th semester onwards, beyond the college curriculum
• Presented my final year thesis at a conference (SPIN, 2015): https://ieeexplore.ieee.org/document/7095417
• Walked away with an offer from Snapdeal (the highest placement that year in NIT Rourkela) and a lot of experience and learning