Data Engineer

We are seeking a skilled AWS ETL/ELT Data Architect with a specialization in MongoDB to join our team. The ideal candidate will possess comprehensive knowledge and hands-on experience

in designing, implementing, and managing ETL/ELT processes within AWS while also demonstrating proficiency in MongoDB database management.

This role requires expertise in data architecture, AWS services, and MongoDB to optimize data solutions effectively.

Responsibilities:

● Design, architect, and implement ETL/ELT processes within AWS, integrating data from various sources into data lakes or warehouses, and utilising MongoDB as part of the data ecosystem.

● Collaborate cross-functionally to assess data requirements, analyze sources, and strategize effective data integration within AWS environments, considering MongoDB's role in the architecture.

● Construct scalable and high-performance data pipelines within AWS while integrating MongoDB for optimal data storage, retrieval, and manipulation.

● Develop comprehensive documentation covering data architecture, flows, and the interplay between AWS services, MongoDB, and ETL/ELT processes from scratch.

● Perform thorough data profiling, validation, and troubleshooting, ensuring data accuracy, consistency, and integrity in conjunction with MongoDB management.

● Stay updated with AWS and MongoDB best practices, emerging technologies, and industry trends to propose innovative data solutions and implementations.

● Provide mentorship to junior team members and foster collaboration with stakeholders to deliver robust data solutions.

● Analyze data issues, identify and articulate the business impact of data problems

● Perform code reviews and ensure that all solutions are aligned with pre-defined architectural standards, guidelines, and best practices, and meet quality standards

Qualifications:

● Bachelor's or Master’s degree in Computer Science, Information Technology, or related field.

● Minimum 5 years of hands-on experience in ETL/ELT development, data architecture, or similar roles.

● Having implemented more than a minimum of 3-4 live projects in a similar field would be desirable.

● Expertise in designing and implementing AWS-based ETL/ELT processes using tools like AWS Glue, AWS Data Pipeline, etc.

RESPONSIBILITIES:

 Requirement understanding and elicitation, analyze, data/workflows, contribute to product

project and Proof of concept (POC)

 Contribute to prepare design documents and effort estimations.

 Develop AI/ML Models using best in-class ML models.

 Building, testing, and deploying AI/ML solutions.

 Work with Business Analysts and Product Managers to assist with defining functional user

stories.

 Ensure deliverables across teams are of high quality and clearly documented. 

 Recommend best ML practices/Industry standards for any ML use case.

 Proactively take up R and D and recommend solution options for any ML use case.

REQUIREMENTS:

Required Skills

 Overall experience of 4 to 7 Years working on AI/ML framework development

 Good programming knowledge in Python is must.

 Good Knowledge of R and SAS is desired.

 Good hands on and working knowledge SQL, Data Model, CRISP-DM.

 Proficiency with Uni/multivariate statistics, algorithm design, and predictive AI/ML modelling.

 Strong knowledge of machine learning algorithms, linear regression, logistic regression, KNN,

Random Forest, Support Vector Machines and Natural Language Processing.

 Experience with NLP and deep neural networks using synthetic and artificial data.

 Involved in different phases of SDLC and have good working exposure on different SLDC’s like

Agile Methodologies.

• Your responsibilities:
• Build, improve and extend NLP capabilities
• Research and evaluate different approaches to NLP problems
• Must be able to write code that is well designed, produce deliverable results
• Write code that scales and can be deployed to production

• Fundamentals of statistical methods is a must
• Experience in named entity recognition, POS Tagging, Lemmatization, vector representations of textual data and neural networks - RNN, LSTM
• A solid foundation in Python, data structures, algorithms, and general software development skills.
• Ability to apply machine learning to problems that deal with language
• Engineering ability to build robustly scalable pipelines
• Ability to work in a multi-disciplinary team with a strong product focus

About CarWale: CarWale's mission is to bring delight in car buying, we offer a bouquet of reliable tools and services to help car consumers decide on buying the right car, at the right price and from the right partner. CarWale has always strived to serve car buyers and owners in the most comprehensive and convenient way possible. We provide a platform where car buyers and owners can research, buy, sell and come together to discuss and talk about their cars.We aim to empower Indian consumers to make informed car buying and ownership decisions with exhaustive and un-biased information on cars through our expert reviews, owner reviews, detailed specifications and comparisons. We understand that a car is by and large the second-most expensive asset a consumer associates his lifestyle with! Together with CarTrade & BikeWale, we are the market leaders in the personal mobility media space.About the Team:We are a bunch of enthusiastic analysts assisting all business functions with their data needs. We deal with huge but diverse datasets to find relationships, patterns and meaningful insights. Our goal is to help drive growth across the organization by creating a data-driven culture.

We are looking for an experienced Data Scientist who likes to explore opportunities and know their way around data to build world class solutions making a real impact on the business. 

Skills / Requirements –

• 3-5 years of experience working on Data Science projects
• Experience doing statistical modelling of big data sets
• Expert in Python, R language with deep knowledge of ML packages
• Expert in fetching data from SQL
• Ability to present and explain data to management
• Knowledge of AWS would be beneficial
• Demonstrate Structural and Analytical thinking
• Ability to structure and execute data science project end to end

Education –

Bachelor’s degree in a quantitative field (Maths, Statistics, Computer Science). Masters will be preferred.