Data Engineer Job Vacancy in Collinson Mumbai, Maharashtra – Updated today

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Full Details :
Company Name : Collinson
Location : Mumbai, Maharashtra
Position :

Job Description : Job Location – Hong Kong, Singapore, India, or Australia
Company
Collinson is a global leader in loyalty and benefits. We use our expertise and products to craft customer experiences which enable some of the world’s best-known brands to acquire, engage and retain the most demanding and choice-rich customers.
We are the trusted partner behind many of the world’s leading financial services, airline, hotel and retail brand’s loyalty initiatives, customer benefits and reward programmes. Our solutions drive more profitable customer relationships, enrich their travel experiences, protect what matters and assist in times of need. Our solutions include loyalty services, airport lounge access, airport experiences, travel insurance, health solutions, travel risk management, flight disruption assistance
We take our 30 years’ experience working with household names such as American Express, Visa, Mastercard, Avios, Flying Blue, BA, Asia Miles and Radisson Blue, in over 170 countries, and help our clients to deliver the smarter experiences it takes to differentiate their propositions, and help them win deeper devotion from their customers. Collinson is a privately-owned entrepreneurial business with 2,000+ passionate people working in 20 locations worldwide.
Purpose of the job
As a Data Engineer, you will support data scientists, data analysts and other peers from technical team by enabling data solutions that can be developed rapidly and maintained easily while solving business problems. This is more than building and maintaining ETL pipelines. The role requires skills to deliver big data solutions with common characteristics such as flawless availability, quality, reliability performance and scaling.
This new role will operate within Data Insight department who configure, implement, and maintain advanced analytics products, managed analytics services, integration & automation and marketing automation solutions for our business and clients within Asia Pacific region. The role will span across loyalty (retail, financial services and hospitality), travel experiences (airlines & lounges).

Key Responsibilities
Represent data engineering function at all stages of projects (scoping, planning, development, quality control, production)Continuous R&D of latest data engineering concepts; enhance existing solutionsScope and estimate effort needed to stand up and maintain data infrastructureWork with central devops teams to ensure best practise is followedDesign, build and ongoing maintenance of data solutions ensuring they are clean, valid, maintainable, usable at scale and sustainable for additions and improvementsDecide on the required data infrastructure to run onDrive the adoption and use of infrastructure as code into the teamProvide recommendations for developing batch and real-time analytical solutions, develop prototypes and proof of concepts for enterprise solutionsBuild scalable, highly performant infrastructure, tools, and frameworks for delivering clear business insights from a variety of raw data sourcesImplement complex analytical solutions with a focus on collecting, parsing, managing, analysing, and visualising large data setsMigrate and modernise existing data solutions to the new data platformWork with business teams to understand and define clear data solution requirementsBuild strong relationships with stakeholders with a view to providing high-value solutions within the business whilst keeping communication channels always openDocument proof of concepts, data solutions and all source-to-target mappingsSupport in life solutions as required
Knowledge, skills and experience required
Skills and Knowledge
AWS (EC2, Lambda, EMR, SageMaker, RDS, DynamoBD, Redshift, Athena, Kinesis, S3, CloudFormation, CloudWatch, API Gateway)Advanced Python, PySpark and SQLSnowflake is also desirableBash, Hive, Apache, Atlas, Ranger, NiFiAPI integration with 3rd party software and data sourcesData lakesBusiness Intelligence tools: Tableau, Alteryx, PlotlyApplication of CI/CD tools and frameworksData architecture and design principlesPresenting complex concept in an easy-to-understand ways to both tech and non-tech audiences; A confident and articulate communicator in EnglishData technology landscape, how to apply this to business problems and identify the limitationsStrong working knowledge on the mechanics of the underlying Machine Learning algorithmsExpert in Relational and NoSQL data modeling and databases, file formats such as: Parquet, JSON, CSV and how to apply different data modalities for the appropriate use cases
Experience
At least 3 years commercial hands-on experience as a Data Engineer across at least one of the following disciplines: consumer loyalty, travel & hospitality, retail (shopping mall brands), financial services (neo banks or e-commerce)Scoping and estimating data engineering tasksBuilding complex distributed batch and real-time data solutions which are consumable by machine learning models (segmentation, recommender & NLP) and data visualisations tools (Tableau)End-to-end delivery of data solutionsWorking with version control systems (e.g. Git, AWS CodeCommit)Working with external vendors, remote teams in different time zonesBSc degree in corresponding fields

Person Specification
Self-starter with can-do, will-do attitudeAble to work with minimal supervision and oversight, able to overcome challenges independentlyLifelong learner – always identifying areas of improvement and staying up to date with evolving technology and business landscapeAble to work at pace while working through frequently changing priorities and challenges in a collegiate wayWith strong character and presence – capable of handling and challenging tough and demanding clients and stakeholders in a respectful and productive manorAlways challenging ambiguityCollaborative and a strong team playerNimble, open-minded thinking, process advocate but committed to impactThorough and attentive to detailWell planned and organised

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