Engineer III - Data Engineer

Posted 4 Days Ago
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Gurugram, Haryana, IND
In-Office
Senior level
Information Technology
The Role
Designs and operates production data pipelines, ingestion and scraping systems, distributed processing architectures, APIs, caching services, and data-quality frameworks. The role uses Python, Spark, cloud data platforms, workflow orchestration, SQL, NoSQL systems, Kubernetes, and observability tools. It includes production ownership, incident response, technical documentation, code reviews, mentoring, and collaboration with data science and platform teams to support machine-learning and forecasting systems.
Summary Generated by Built In

At Anaplan, we are a team of innovators focused on optimizing business decision-making through our leading AI-infused scenario planning and analysis platform so our customers can outpace their competition and the market.

What unites Anaplanners across teams and geographies is our collective commitment to our customers’ success and to our Winning Culture.

Our customers rank among the who’s who in the Fortune 50. Coca-Cola, LinkedIn, Adobe, LVMH and Bayer are just a few of the 2,400+ global companies who rely on our best-in-class platform.

Our Winning Culture is the engine that drives our teams of innovators. We champion diversity of thought and ideas, we behave like leaders regardless of title, we are committed to achieving ambitious goals, and we love celebrating our wins – big and small.

Supported by operating principles of being strategy-led, values-based and disciplined in execution, you’ll be inspired, connected, developed and rewarded here. Everything that makes you unique is welcome; join us and let’s build what’s next - together!

What you'll do
  • Data Pipeline & Orchestration: Design, build, and run batch and scheduled data pipelines (Airflow, Dagster, Prefect) and lead orchestrator upgrades.
  • Data Ingestion & Scraping: Own and extend data collectors and engines, including web/API ingestion, large-scale web scraping (Playwright, Selenium, Scrapy), parsing, normalization, and file merging.
  • Distributed Processing: Build scalable distributed processing architectures (Spark on EMR, Databricks, Dataproc) and analytical query layers (Athena, Snowflake, BigQuery), including cross-cloud ingestion pipelines.
  • Caching & Entity Matching: Improve entity matching and caching services (Redis, MemoryDB, DynamoDB) to optimize accuracy, latency, and operational cost.
  • Data Access & APIs: Develop and maintain high-performance Python dataaccess layers and APIs for downstream ML and product teams.
  • Data Quality & Observability: Own data quality initiatives, including validation frameworks, retention policies, backfills, monitoring, and OpenTelemetry-based observability.
  • Cross-Functional Collaboration: Partner with data science, forecasting, and platform teams to ship features safely behind feature flags (LaunchDarkly, Unleash).
  • Engineering Leadership: Raise engineering standards across the team through rigorous code reviews, technical design documents, and mentoring.
What you bring
  • Experience: 6+ years of software or data engineering experience, including 3+ years of experience building and maintaining production data pipelines.
  • Python Mastery: Strong Python development skills with a commitment to writing clean, tested code (using pytest, nox, or tox).
  • Orchestration Expertise: Deep experience with workflow orchestration (Airflow DAG design, operators, scheduling, and failure handling) or modern alternatives like Dagster and Prefect.
  • Data Ecosystems: Hands-on experience with distributed compute (Spark) and cloud data ecosystems (AWS EMR/Athena/S3, Databricks, Snowflake, GCP).
  • Storage & Modeling: Solid SQL and data-modeling skills, alongside practical experience with NoSQL databases, caching layers, and message queues (MongoDB, Redis, Kafka, RabbitMQ).
  • Infrastructure Familiarity: Comfort deploying and managing containerized workloads on Kubernetes using Docker and Helm.
  • Production Ownership: A proven track record of owning production pipelines, including participating in on-call rotations, incident response, and root-cause analysis.
  • Communication: Clear written technical communication and a history of documenting architectural decisions.
Nice to have
  • Scraping Infrastructure: Experience managing large-scale web datacollection and distributed crawler infrastructure.
  • Data Science / ML Concepts: Familiarity with record linkage, entity resolution, fuzzy matching, and NLP preprocessing (spaCy, NLTK).
  • Multi-Cloud Pipelines: Hands-on experience building multi-cloud datapipelines (e.g., bridging GCP/BigQuery and AWS).
  • ML Ops: Experience designing data pipelines that directly feed machine learning or forecasting systems.
 

Our Commitment to Diversity, Equity, Inclusion and Belonging (DEIB)

We believe attracting and retaining the best talent and fostering an inclusive culture strengthens our business. DEIB improves our workforce, enhances trust with our partners and customers, and drives business success. Build your career in a place where diversity, equity, inclusion and belonging aren’t just words on paper – this is what drives our innovation, it’s how we connect, and it contributes to what makes us a market leader. We believe in a hiring and working environment where all people are respected and valued, regardless of gender identity or expression, sexual orientation, religion, ethnicity, age, neurodiversity, disability status, citizenship, or any other aspect which makes people unique. We hire you for who you are, and we want you to bring your authentic self to work every day! 

We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, perform essential job functions, and receive equitable benefits and all privileges of employment. Please contact us to request accommodation.  

Fraud Recruitment Disclaimer  

It has come to our attention that fraudulent and fictitious job opportunities are being circulated on the Internet. Prospective candidates are being contacted by certain individuals, mainly through telephone calls, emails and correspondence, claiming they are representatives of Anaplan. The main purpose of these correspondences and announcements is to obtain privileged information from individuals.  

Anaplan does not:  

  • Extend offers to candidates without an extensive interview process with a member of our recruitment team and a hiring manager via video or in person.   
  • Send job offers via email. All offers are first extended verbally by a member of our internal recruitment team whenever possible and then followed up via written communication.  

All emails from Anaplan would come from an @anaplan.com email address. Should you have any doubts about the authenticity of an email, letter or telephone communication purportedly from, for, or on behalf of Anaplan, please send an email to [email protected] before taking any further action in relation to the correspondence.   

Privacy & AI Notice

Candidate data processed during our recruitment activities is handled in accordance with our Candidate Privacy Notice. This may include the use of artificial intelligence or automated tools to assist our team in evaluating qualifications.


Skills Required

  • 6+ years of software or data engineering experience
  • 3+ years building and maintaining production data pipelines
  • Strong Python development skills and clean, tested code practices
  • Deep experience with workflow orchestration, including Airflow, Dagster, or Prefect
  • Hands-on experience with distributed compute such as Spark and cloud data ecosystems including AWS, Databricks, Snowflake, or GCP
  • Solid SQL and data-modeling skills
  • Experience with NoSQL databases, caching layers, and message queues
  • Experience deploying and managing containerized workloads on Kubernetes using Docker and Helm
  • Track record of owning production pipelines, on-call rotations, incident response, and root-cause analysis
  • Clear written technical communication and experience documenting architectural decisions
  • Experience managing large-scale web data collection and distributed crawler infrastructure
  • Familiarity with record linkage, entity resolution, fuzzy matching, and NLP preprocessing
  • Experience building multi-cloud data pipelines
  • Experience designing data pipelines that feed machine-learning or forecasting systems

Anaplan Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Anaplan and has not been reviewed or approved by Anaplan.

  • Strong & Reliable Incentives — Earnings potential in sales is considered good or fair, with on‑target earnings achievable when plans are met. This indicates variable pay can meaningfully boost total compensation when targets are hit.
  • Healthcare Strength — Medical, dental, and vision coverage are described as strong, complemented by mental‑health resources and EAP support. Company‑wide paid wellbeing days reinforce the health and wellness focus.
  • Parental & Family Support — Equitable parental and caregiver leave are highlighted alongside fertility and adoption support. Family‑forming programs such as Carrot are part of the offering.

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The Company
HQ: Miami, FL
2,194 Employees
Year Founded: 2006

What We Do

Anaplan is building a future where connected leaders and teams are able to constantly adapt, transform and reinvent their businesses. We make it possible to share actionable insights, empower and unleash creativity, and drive innovation. With Anaplan, finance and operational leaders across the organization can model complex scenarios, forecast continuously with added intelligence, and make agile decisions with confidence.

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