Data engineer - Machine learning

Data Engineer- Senior

Cubera is a data company revolutionizing big data analytics and Adtech through data share value principles wherein the users entrust their data to us. We refine the art of understanding, processing, extracting, and evaluating the data that is entrusted to us. We are a gateway for brands to increase their lead efficiency as the world moves towards web3.

What are you going to do?

Design & Develop high performance and scalable solutions that meet the needs of our customers.

Closely work with the Product Management, Architects and cross functional teams.

Build and deploy large-scale systems in Java/Python.

Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.

Create data tools for analytics and data scientist team members that assist them in building and optimizing their algorithms.

Follow best practices that can be adopted in Bigdata stack.

Use your engineering experience and technical skills to drive the features and mentor the engineers.

What are we looking for ( Competencies) :

Bachelor’s degree in computer science, computer engineering, or related technical discipline.

Overall 5 to 8 years of programming experience in Java, Python including object-oriented design.

Data handling frameworks: Should have a working knowledge of one or more data handling frameworks like- Hive, Spark, Storm, Flink, Beam, Airflow, Nifi etc.

Data Infrastructure: Should have experience in building, deploying and maintaining applications on popular cloud infrastructure like AWS, GCP etc.

Data Store: Must have expertise in one of general-purpose No-SQL data stores like Elasticsearch, MongoDB, Redis, RedShift, etc.

Strong sense of ownership, focus on quality, responsiveness, efficiency, and innovation.

Ability to work with distributed teams in a collaborative and productive manner.

Benefits:

Competitive Salary Packages and benefits.

Collaborative, lively and an upbeat work environment with young professionals.

Job Category: Development

Job Type: Full Time

Job Location: Bangalore

Job Responsibilities:-

• Develop robust, scalable and maintainable machine learning models to answer business problems against large data sets.
• Build methods for document clustering, topic modeling, text classification, named entity recognition, sentiment analysis, and POS tagging.
• Perform elements of data cleaning, feature selection and feature engineering and organize experiments in conjunction with best practices.
• Benchmark, apply, and test algorithms against success metrics. Interpret the results in terms of relating those metrics to the business process.
• Work with development teams to ensure models can be implemented as part of a delivered solution replicable across many clients.
• Knowledge of Machine Learning, NLP, Document Classification, Topic Modeling and Information Extraction with a proven track record of applying them to real problems.
• Experience working with big data systems and big data concepts.
• Ability to provide clear and concise communication both with other technical teams and non-technical domain specialists.
• Strong team player; ability to provide both a strong individual contribution but also work as a team and contribute to wider goals is a must in this dynamic environment.
• Experience with noisy and/or unstructured textual data.

knowledge graph and NLP including summarization, topic modelling etc

• Strong coding ability with statistical analysis tools in Python or R, and general software development skills (source code management, debugging, testing, deployment, etc.)
• Working knowledge of various text mining algorithms and their use-cases such as keyword extraction, PLSA, LDA, HMM, CRF, deep learning & recurrent ANN, word2vec/doc2vec, Bayesian modeling.
• Strong understanding of text pre-processing and normalization techniques, such as tokenization,
• POS tagging and parsing and how they work at a low level.
• Excellent problem solving skills.
• Strong verbal and written communication skills
• Masters or higher in data mining or machine learning; or equivalent practical analytics / modelling experience
• Practical experience in using NLP related techniques and algorithms
• Experience in open source coding and communities desirable.

Able to containerize Models and associated modules and work in a Microservices environment

• Play a critical role as a member of the leadership team in shaping and supporting our overall company vision, day-to-day operations, and culture.
• Set the technical vision and build the technical product roadmap from launch to scale; including defining long-term goals and strategies
• Define best practices around coding methodologies, software development, and quality assurance
• Define innovative technical requirements and systems while balancing time, feasibility, cost and customer experience
• Build and support production products
• Ensure our internal processes and services comply with privacy and security regulations
• Establish a high performing, inclusive engineering culture focused on innovation, execution, growth and development
• Set a high bar for our overall engineering practices in support of our mission and goals
• Develop goals, roadmaps and delivery dates to help us scale quickly and sustainably
• Collaborate closely with Product, Business, Marketing and Data Science
• Experience with financial and transactional systems
• Experience engineering for large volumes of data at scale
• Experience with financial audit and compliance is a plus
• Experience building a successful consumer facing web and mobile apps at scale

Company Profile:

Easebuzz is a payment solutions (fintech organisation) company which enables online merchants to accept, process and disburse payments through developer friendly APIs. We are focusing on building plug n play products including the payment infrastructure to solve complete business problems. Definitely a wonderful place where all the actions related to payments, lending, subscription, eKYC is happening at the same time.

We have been consistently profitable and are constantly developing new innovative products, as a result, we are able to grow 4x over the past year alone. We are well capitalised and have recently closed a fundraise of $4M in March, 2021 from prominent VC firms and angel investors. The company is based out of Pune and has a total strength of 180 employees. Easebuzz’s corporate culture is tied into the vision of building a workplace which breeds open communication and minimal bureaucracy. An equal opportunity employer, we welcome and encourage diversity in the workplace. One thing you can be sure of is that you will be surrounded by colleagues who are committed to helping each other grow.

Easebuzz Pvt. Ltd. has its presence in Pune, Bangalore, Gurugram.

Salary: As per company standards.

Designation: Data Engineering

Location: Pune

Experience with ETL, Data Modeling, and Data Architecture

Design, build and operationalize large scale enterprise data solutions and applications using one or more of AWS data and analytics services in combination with 3rd parties
- Spark, EMR, DynamoDB, RedShift, Kinesis, Lambda, Glue.

Experience with AWS cloud data lake for development of real-time or near real-time use cases

Experience with messaging systems such as Kafka/Kinesis for real time data ingestion and processing

Build data pipeline frameworks to automate high-volume and real-time data delivery

Create prototypes and proof-of-concepts for iterative development.

Experience with NoSQL databases, such as DynamoDB, MongoDB etc

Create and maintain optimal data pipeline architecture,

Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.

Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS ‘big data’ technologies.

Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics.

Work with stakeholders including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs.

Keep our data separated and secure across national boundaries through multiple data centers and AWS regions.

Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader.

Evangelize a very high standard of quality, reliability and performance for data models and algorithms that can be streamlined into the engineering and sciences workflow

Build and enhance data pipeline architecture by designing and implementing data ingestion solutions.

Employment Type

Full-time

We are looking for an outstanding Big Data Engineer with experience setting up and maintaining Data Warehouse and Data Lakes for an Organization. This role would closely collaborate with the Data Science team and assist the team build and deploy machine learning and deep learning models on big data analytics platforms.

Roles and Responsibilities:

• Develop and maintain scalable data pipelines and build out new integrations and processes required for optimal extraction, transformation, and loading of data from a wide variety of data sources using 'Big Data' technologies.
• Develop programs in Scala and Python as part of data cleaning and processing.
• Assemble large, complex data sets that meet functional / non-functional business requirements and fostering data-driven decision making across the organization.  
• Responsible to design and develop distributed, high volume, high velocity multi-threaded event processing systems.
• Implement processes and systems to validate data, monitor data quality, ensuring production data is always accurate and available for key stakeholders and business processes that depend on it.
• Perform root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
• Provide high operational excellence guaranteeing high availability and platform stability.
• Closely collaborate with the Data Science team and assist the team build and deploy machine learning and deep learning models on big data analytics platforms.

Skills:

• Experience with Big Data pipeline, Big Data analytics, Data warehousing.
• Experience with SQL/No-SQL, schema design and dimensional data modeling.
• Strong understanding of Hadoop Architecture, HDFS ecosystem and eexperience with Big Data technology stack such as HBase, Hadoop, Hive, MapReduce.
• Experience in designing systems that process structured as well as unstructured data at large scale.
• Experience in AWS/Spark/Java/Scala/Python development.
• Should have Strong skills in PySpark (Python & SPARK). Ability to create, manage and manipulate Spark Dataframes. Expertise in Spark query tuning and performance optimization.
• Experience in developing efficient software code/frameworks for multiple use cases leveraging Python and big data technologies.
• Prior exposure to streaming data sources such as Kafka.
• Should have knowledge on Shell Scripting and Python scripting.
• High proficiency in database skills (e.g., Complex SQL), for data preparation, cleaning, and data wrangling/munging, with the ability to write advanced queries and create stored procedures.
• Experience with NoSQL databases such as Cassandra / MongoDB.
• Solid experience in all phases of Software Development Lifecycle - plan, design, develop, test, release, maintain and support, decommission.
• Experience with DevOps tools (GitHub, Travis CI, and JIRA) and methodologies (Lean, Agile, Scrum, Test Driven Development).
• Experience building and deploying applications on on-premise and cloud-based infrastructure.
• Having a good understanding of machine learning landscape and concepts. 

Qualifications and Experience:

Engineering and post graduate candidates, preferably in Computer Science, from premier institutions with proven work experience as a Big Data Engineer or a similar role for 3-5 years.

Certifications:

Good to have at least one of the Certifications listed here:

    AZ 900 - Azure Fundamentals

    DP 200, DP 201, DP 203, AZ 204 - Data Engineering

    AZ 400 - Devops Certification