Sr. Data Engineer

Title: Sr. Data Engineer

Location: Gurgaon, India

Type: (Hybrid, In-Office)                           

Job Description

Who We Are

Fareportal is a travel technology company powering a next-generation travel concierge service. Utilizing its innovative technology and company owned and operated global contact centres, Fareportal has built strong industry partnerships providing customers access to over 500 airlines, a million lodgings, and hundreds of car rental companies around the globe. With a portfolio of consumer travel brands including CheapOair and OneTravel, Fareportal enables consumers to book-online, on mobile apps for iOS and Android, by phone, or live chat. Fareportal provides its airline partners with access to a broad customer base that books high-yielding international travel and add-on ancillaries.

HIGHLIGHTS:

  • Fareportal is the number 1 privately held online travel company in flight volume.
  • Fareportal partners with over 500 airlines, 1 million lodgings, and hundreds of car rental companies worldwide.
  • 2019 annual sales exceeded $5 billion.
  • Fareportal sees over 150 million unique visitors annually to our desktop and mobile sites.
  • Fareportal, with its global workforce of over 2,600 employees, is strategically positioned with 9 offices in 6 countries and headquartered in New York City.

Role Overview

We are looking for a Sr. Data Engineer to create and maintain large-scale data pipelines for structured and unstructured data. You will work across modern cloud-based architectures to enable analytics, machine learning and business intelligence.

Data Engineers are at the heart of how Fareportal works, and they are part software engineers and part database experts. You will focus on creating and supporting large scale pipelines that we deploy to power our analytics, recommendation, pricing or other systems. The ideal candidate will participate in the design and implementation of the entire data pipeline, from project ideation, figuring out which data to capture and store, coming up with architectures, to creating the final data flows and monitoring.

We are passionate about making data-driven decisions and you will have the opportunity to shape the team’s direction and create large impact.

Responsibilities

  • Support our data modeling efforts to ensure we are capturing the data needed to improve our modeling and analytic capabilities
  • Develop and maintain data applications in Python across various data formats and architectures, including:
    • SQL, Clickhouse, Elastic, MongoDB, AWS S3, Azure App Insights, csv, JSON, parquet, Protobuf
    • Airflow, Docker, Bash, SFTP, AWS Lambda, ECS
  • Evaluate and ensure data integrity across various formats through mature, high-quality, well-organized application code with fully developed unit and integration testing and telemetry
  • Collaborate with data scientists and analysts to ensure data accessibility for AI/ML models.
  • Build and optimize scalable data workflows using modern cloud tools (e.g. Azure Data Factory)
  • Implement DataOps best practices, ensuring end-to-end pipeline monitoring and observability.

Our ideal candidate:

Who You Are

  • You are smart and love to build systems that are well tested as well as flexible.
  • You like being around smart people who will challenge you on a daily basis.
  • You love to ramp up on new technologies to build awesome things with us!
  • Passionate about working with large unstructured and structured data sets and developing new approaches to relevance problems.
  • You like to share your knowledge and guide other fellow data engineers and scientists.

Requirements

  • 4+ years’ experience developing, maintaining, and testing big data pipelines.
  • A strong technical advocate with a background in Python + SQL. Preferably familiar with both on-prem and cloud data systems, for example, AWS or Azure; SQL and NoSQL.
  • Experience with shell scripting and Unix command line, as well as virtual environments.
  • Strong understanding of data modeling and ETL / ELT best practices.
  • Proficiency in building and optimizing data pipelines with Python.
  • Familiarity with stream processing frameworks like Apache Kafka, Spark Streaming, or Flink.
  • Knowledge of containerization (Docker, Kubernetes) and orchestration tools (Airflow, Prefect).

Nice to have:

  • Experience with CI/CD infrastructure and a strong supporter of unit / integration testing.
  • Experience with Docker, VMs and container technologies (ie Kubernetes).
Job Category: Data
Job Type: Full Time
Job Location: Gurgaon

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