Data Scientist III

Jobtailor; Gurugram District; On-site; INR 1,500,000 - 2,500,000; Full time

Benefits offered by this job

Health care coverage

Generous time off

Continuous learning resources

Retirement planning

Financial wellness programs

Family friendly perks

Job summary

Dormont Manufacturing Co located in Gurugram District, Haryana, seeks a data engineering professional to architect and build scalable, production-grade data products.

This role requires at least 7 years of experience across data engineering and machine learning, with a focus on enabling data-driven insights through advanced analytics.

Join a dynamic team that values experimentation and continuous learning, offering significant visibility and growth opportunities.

Qualifications

• 7+ years of experience in data engineering and machine learning.
• Experience with Databricks/Spark and relevant certifications preferred.
• Experience in building production-grade data pipelines in a cloud environment.

Responsibilities

• Architect data lake/lakehouse platforms for analytics.
• Lead cloud event-driven architecture integrations.
• Design and optimize ETL/ELT pipelines for operational workloads.

Skills

Expert SQL

Strong Python

Hands-on PySpark

Solid data modeling

Education

Bachelor's degree in Computer Science, Engineering, Statistics, Mathematics, or related field

Master's degree

Tools

Databricks

Cloud-native architectures

Job description

We are a central data and reporting function that gathers all organizational data spanning from financial to inventory. This unique position allows our team to innovate and build data products and solutions for internal stakeholders, including applying AI and Machine Learning to our comprehensive datasets. We foster a collaborative environment where continuous learning is encouraged, and team members regularly share knowledge about the latest AI developments and methodologies. The team values experimentation, data-driven decision making, and maintains a culture of intellectual curiosity where interns are mentored by experienced practitioners and given meaningful projects that contribute to real-world applications.

The Impact:

This role is critical because it turns the organization’s unified data into scalable, production-grade data products—enabling accurate forecasting, early anomaly detection, and smarter risk decisions that directly improve operational efficiency and financial outcomes.

What’s in it for you:

Opportunity to design and own a modern, end-to-end Databricks lakehouse platform, working at the intersection of data engineering, architecture, and applied AI/ML.

High visibility role with exposure to senior stakeholders, business leaders, and decision-makers, directly influencing strategy through data-driven insights.

Strong growth environment with hands‑on experience in cutting‑edge technologies and continuous learning through collaboration and mentorship.

Chance to work on enterprise-wide, high-impact data products with a global scope, enabling innovation across diverse business domains and markets.

Years of Experience and Qualification:

Typically, you’ll bring 7+ years of experience in data engineering, machine learning, and building production‑grade data pipelines and platforms in a cloud environment. A bachelor’s degree in Computer Science, Engineering, Statistics, Mathematics, or a related field is required; a master’s degree is a plus.

Preferred qualifications include experience with Databricks/Spark and lakehouse architectures, along with relevant cloud certifications (e.g., Azure, AWS, GCP data engineering) or Databricks certifications.

Responsibilities:

Architect data lake/lakehouse platforms for forecasting, anomaly detection, and BI/analytics using Databricks, Spark, and Delta‑style patterns.

Set and enforce engineering standards for data modeling, integration, and pipeline design across teams/products.

Lead cloud event‑driven/microservices architecture that integrates with web front‑ends and APIs.

Design, build, and optimize batch and event‑driven ELT/ETL pipelines for analytical and operational workloads.

Build ingestion/transformation flows aligned to bronze/silver/gold, with validation, CI/CD, testing, and observability baked in.

Advanced Analytics, Forecasting & Anomaly Detection

Implement scalable time‑series forecasting training and inference across categories.

Build model monitoring (RMSE/MAE/bias/coverage/residuals) with dashboards and automated alerts.

Develop residual/outlier detection using Z‑scores, PELT change points, and confidence‑interval breach checks.

Implement classification/risk‑scoring models (e.g., Logistic Regression, Random Forest, XGBoost, clustering, HMMs) for anomaly classification and category risk.

Data Quality, Schema & Drift Monitoring

Automate data quality and schema validation (missing dates/targets, type changes, schema evolution, allocation shifts).

Detect drift in data and model behavior (e.g., allocation stability, category mix changes).

Deliver per‑category anomaly flags and summarized insights for decision‑makers.

Provide technical leadership (code/design reviews, mentoring, knowledge sharing) for engineers and data scientists.

Collaborate with product/UX/business to refine requirements, prioritize work, and plan roadmaps.

Champion engineering excellence: quality, performance, and operational readiness.

What We’re Looking For:

Core Data & Engineering

• Expert SQL (complex joins, window functions, performance tuning at scale).
• Strong Python for data processing, APIs/microservices, and analytics.
• Hands‑on PySpark for large‑scale distributed processing and ETL/ELT.
• Solid data modeling (dimensional models, star/snowflake schemas, medallion design).

Data Platforms & Cloud

• Proven Databricks experience (notebooks, jobs, clusters, Delta tables) and lakehouse architectures.
• Strong grasp of cloud‑native, event‑driven architectures (queues, event buses, serverless triggers) for data/ML workflows.
• Experience designing/operating microservices exposing REST/gRPC APIs for forecasting and analytics.

Statistical Modeling & ML

• Hands‑on, production experience with time‑series forecasting (ARIMA or similar).
• Applied anomaly detection/classification: residual analysis, Z‑score, PELT, Logistic Regression, Random Forest, XGBoost, clustering, HMMs.
• Familiarity with end‑to‑end predictive analytics, including model validation and monitoring.

Monitoring, Quality & MLOps

• Experience building monitoring for models/pipelines (metrics, dashboards, alerts), focused on error trends and drift.
• Strong background in production data quality and schema monitoring, including automated checks/guardrails.
• Familiar with CI/CD, version control, testing, and observability for data/ML systems.

Web & Integration

• Experience integrating data/ML back‑end services with web front‑ends (APIs, payloads, error handling).
• Understanding of authentication, authorization, and security for data/ML APIs in the cloud.

Technical Leadership

• Lead design discussions, set standards, and mentor engineers/data scientists.
• Comfortable with product/business/UX; turn ambiguity into clear technical roadmaps.
• Explain trade‑offs/metrics to non‑technical stakeholders; strong documentation habits.
• Analytical approach to data quality, drift, and performance issues; pragmatic solutions.
• Takes end‑to‑end responsibility—from design/implementation to monitoring and improvement in production.
• Work cross‑functionally, support research teams/interns, and elevate engineering/analytics maturity.
• Iterate through MVPs, experiment when justified, and adapt to evolving priorities.

Our Benefits

• Health & Wellness: Health care coverage designed for the mind and body.
• Flexible Downtime: Generous time off helps keep you energized for your time on.
• Continuous Learning: Access a wealth of resources to grow your career and learn valuable new skills.
• Invest in Your Future: Secure your financial future through competitive pay, retirement planning, a continuing education program with a company‑matched student loan contribution, and financial wellness programs.
• Family Friendly Perks: It’s not just about you. S&P Global has perks for your partners and little ones, too, with some best‑in‑class benefits for families.
• Beyond the Basics: From retail discounts to referral incentive awards—small perks can make a big difference.

Equal Opportunity Employer

S&P Global is an equal opportunity employer and all qualified candidates will receive consideration for employment without regard to race/ethnicity, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, marital status, military veteran status, unemployment status, or any other status protected by law. Only electronic job submissions will be considered for employment.

If you need an accommodation during the application process due to a disability, please send an email to: [e-mail] and your request will be forwarded to the appropriate person.