Engineer III - Data Engineer
Anaplan is hiring an Engineer III - Data Engineer in Gurugram, India. Level rates it ; you can apply on Anaplan.
Level's read on this job
- Level rates this data engineer role Works on AI ●●●○: the daily work is on AI products, without building the model.
- The posting mentions Airflow, Dagster and Prefect among its tools and skills.
- Level classes it as a senior role.
- Anaplan has 151 other open roles on Level.
- Posted in the last few days.
AI in this role
Build and scale data pipelines, ingestion engines, and access layers supporting AI-infused scenario planning and analysis platforms.
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.
- 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.
- 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 people@anaplan.com 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.
How we rate this
Engineer III - Data Engineer at Anaplan rates 65 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.
Works on AI. The daily work is on AI products, without building the model.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in data engineer jobs at this level
Pay
- Typical data engineer job
- $150k
This posting doesn't list pay. Use the typical data engineer figure when pay comes up. See data engineer jobs
Questions you could be asked
- How do you monitor a model once it's live, and how do you know it needs retraining?
- What NLP problem have you worked on, and how did you measure whether it actually worked?
- Tell me about a project where data engineering was part of your work. What did you do?
- Tell me about a project where etl was part of your work. What did you do?
- Tell me about a project where distributed systems was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: ML Ops, NLP, Data Engineering, ETL, and Distributed Systems. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.
Want an expert to read your CV for this job?
Free. Send your CV and the role you want next. We reply by email within 2 to 4 business days.
Get new data engineer jobs (Works on AI ●●●○ or higher) by email
One email a week with the new data engineer jobs (Works on AI ●●●○ or higher), each rated for how much AI is in the work. No recruiter spam, unsubscribe in one click.
Free. One email a week. Unsubscribe in one click.
Similar roles
Data roles that work on AI, at other companies.
What kind of AI work fits you?
Answer 12 practical questions in about three minutes. Get a simple profile, the work it points to, and live roles to explore next.
Find my next step