Data & Analytics Systems Engineer
AnaplanGurugram, IndiaPosted 18 March 2026
Job Description
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!
We are looking for a highly skilled and motivated Data and Analytics Systems Engineer to join our growing team. The ideal candidate will have a strong background in data engineering and analytics, with hands-on experience in designing, building, and maintaining data pipelines and analytics solutions. You will be responsible for leveraging a variety of technologies, including Google Cloud Platform, Google BigQuery, Tableau, Informatica, Databricks, Python, and Anaplan, to deliver high-quality data products and insights to our business stakeholders to ensure our Data Analytics systems and operations are effective and efficient.
Requirements
Bachelor's degree in Computer Science, Engineering, or a related field.
5+ years of experience in a data engineering or analytics system management role.
Proven experience with Google Cloud Platform (GCP), including Google BigQuery, Cloud Storage, and Cloud Functions.
Experiences with data visualization tools, preferably Tableau.
Proficiency in ETL/ELT tools like Informatica, Airflow, Dataproc, and so on.
Experience with big data technologies such as Databricks and Spark.
Strong programming skills in Python and experience with data manipulation libraries (e.g., Pandas, NumPy).
Familiarity with the Anaplan platform is a plus.
Excellent problem-solving and communication skills.
Ability to work independently and as part of a team.
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 announcement ... (truncated, view full listing at source)
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