Richard M.

DevOps Engineer

South Delhi, Delhi, India8 yrs 11 mos experience

Most Likely To SwitchHighly Stable

Key Highlights

Expert in building robust data pipelines for finance automation.
Significantly reduced operational costs through strategic governance.
Proficient in both Big Data technologies and Machine Learning.

Stackforce AI infers this person is a Data Engineering expert in Fintech and Data Science sectors.

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Skills

Core Skills

Big DataPythonMachine Learning

Other Skills

Amazon Web Services (AWS)DatabasesApache AirflowSQLApache SparkAWSAirflowData ValidationData ManagementETLAzureHadoopResearchData AnalysisData Modeling

About

Senior Data Engineer with 7+ years of experience in Python & SQL who has extensively worked on & possesses sound understanding in the areas of Big Data(Hadoop/Spark)), ETL workflows, AWS/Azure cloud services, Data Warehousing, Data Modeling, Statistics, Machine Learning & Computer Vision (OpenCV)

Experience

8 yrs 11 mos

Total Experience

2 yrs 2 mos

Average Tenure

3 yrs 11 mos

Current Experience

Paytm

2 roles

Lead Data Engineer

May 2025 – Present · 1 yr

Senior Data Engineer

Jun 2022 – May 2025 · 2 yrs 11 mos

Managed large-scale data computation pipelines, processing Terabytes of data smoothly across EMRs and OLAPs on time, supporting 400+ downstream reports using Python, Apache Spark, Airflow, and AWS
Working closely with finance teams to build robust data pipelines for automating invoicing process for multiple revenue generating verticals of Paytm. This reduced ~1week of finance team's effort to merely hours
Established reconciliation and data validation procedures to accurately early on identify and resolve data discrepancies, safeguarding data integrity across platforms.
Played a key role in significantly reducing AWS operational expenses through strategic data governance policies, optimizing resource management, enabling appropriate data compression techniques and cost-effectiveness platform-wide.
Built a Python framework to onboard datasets and automate lineage creation among those datasets in Datahub. This simplified the process in identifying upstream sources of OLAPs & derive column lineage as well.
Built miscellaneous tools with Python, Bash to improve productivity of engineering team

Amazon Web Services (AWS)DatabasesApache AirflowSQLBig DataPython+1

Fractal

Data Engineer

Jun 2021 – May 2022 · 11 mos · Gurugram, Haryana, India

Leading a team of developers & participating in requirement gathering, grooming, designing architecture & performing code reviews.
Developing ETL flows as Azure web applications to monitor logistics data(TMS, WMS) from different data sources like SAP, SQL & Azure Service bus (queue/message broker) using Python.
Creating microservices in Flask to enable efficient data transfer between multiple different internal stakeholders.
Deploying ETL flows with Docker using Python in a TDD approach.

Amazon Web Services (AWS)DatabasesSQLApache SparkPythonBig Data

Ust

Software Developer

Mar 2019 – Jun 2021 · 2 yrs 3 mos · Noida Area, India

Contract/Vendor Employee role at Adobe
Built a central data repository built for teams across Adobe to run validations & detect outliers on data from different source systems (Hadoop/ HANA/ HBase/ Spark/ SQL Server/ AWS S3/ AWS Redshift) by analysing trend of historical data using ML forecasting algorithms like Prophet, MAD, SARIMA (Time Series Forecasting).
Developed python libraries for inhouse Data Science teams for cleaning data, normalising data & running statistical analysis on their data. This reduced development time & effort by days.
Designed & developed in house automation tool to reduce developer effort & time to update KPIs in existing SQL & HQL scripts.
Built a web based interactive tool to derive SQL/MDX queries from natural language questions that could be utilised to query data from various data sources(kyvos cube, MySQL, Cassandra, HBase)
Translating business' requirements into quantitative queries and collecting/cleaning the necessary data.
Actively involved in data modeling & designing scalable databases for Data Warehouses & Data Marts capable of ETL processes using SQL, Spark (Oozie & Airflow for scheduling)

Amazon Web Services (AWS)DatabasesSQLApache SparkPythonBig Data