Senior Data Engineer

• Mandatory - Hands on experience in Python and PySpark.

• Build pySpark applications using Spark Dataframes in Python using Jupyter notebook and PyCharm(IDE).

• Worked on optimizing spark jobs that processes huge volumes of data.

• Hands on experience in version control tools like Git.

• Worked on Amazon’s Analytics services like Amazon EMR, Lambda function etc

• Worked on Amazon’s Compute services like Amazon Lambda, Amazon EC2 and Amazon’s Storage service like S3 and few other services like SNS.

• Experience/knowledge of bash/shell scripting will be a plus.

• Experience in working with fixed width, delimited , multi record file formats etc.

• Hands on experience in tools like Jenkins to build, test and deploy the applications

• Awareness of Devops concepts and be able to work in an automated release pipeline environment.

• Excellent debugging skills.

Skills

 Job DescriptionPosition: Sr Data Engineer – Databricks & AWS

Experience: 4 - 5 Years

Company Profile:

Exponentia.ai is an AI tech organization with a presence across India, Singapore, the Middle East, and the UK. We are an innovative and disruptive organization, working on cutting-edge technology to help our clients transform into the enterprises of the future. We provide artificial intelligence-based products/platforms capable of automated cognitive decision-making to improve productivity, quality, and economics of the underlying business processes. Currently, we are transforming ourselves and rapidly expanding our business.

Exponentia.ai has developed long-term relationships with world-class clients such as PayPal, PayU, SBI Group, HDFC Life, Kotak Securities, Wockhardt and Adani Group amongst others.

One of the top partners of Cloudera (leading analytics player) and Qlik (leader in BI technologies), Exponentia.ai has recently been awarded the ‘Innovation Partner Award’ by Qlik in 2017.

Get to know more about us on our website: http://www.exponentia.ai/ and Life @Exponentia.

​Role Overview: 

·         A Data Engineer understands the client requirements and develops and delivers the data engineering solutions as per the scope.

·         The role requires good skills in the development of solutions using various services required for data architecture on Databricks Delta Lake, streaming, AWS, ETL Development, and data modeling.

Job Responsibilities

•         Design of data solutions on Databricks including delta lake, data warehouse, data marts and other data solutions to support the analytics needs of the organization.

•         Apply best practices during design in data modeling (logical, physical) and ETL pipelines (streaming and batch) using cloud-based services.

•         Design, develop and manage the pipelining (collection, storage, access), data engineering (data quality, ETL, Data Modelling) and understanding (documentation, exploration) of the data.

•         Interact with stakeholders regarding data landscape understanding, conducting discovery exercises, developing proof of concepts and demonstrating it to stakeholders.

Technical Skills 

•         Has more than 2 Years of experience in developing data lakes, and datamarts on the Databricks platform.

•         Proven skill sets in AWS Data Lake services such as - AWS Glue, S3, Lambda, SNS, IAM, and skills in Spark, Python, and SQL.

•         Experience in Pentaho

•         Good understanding of developing a data warehouse, data marts etc.

•         Has a good understanding of system architectures, and design patterns and should be able to design and develop applications using these principles.

Personality Traits

•         Good collaboration and communication skills

•         Excellent problem-solving skills to be able to structure the right analytical solutions.

•         Strong sense of teamwork, ownership, and accountability

•         Analytical and conceptual thinking 

•         Ability to work in a fast-paced environment with tight schedules.

•         Good presentation skills with the ability to convey complex ideas to peers and management.

Education:

BE / ME / MS/MCA.

Designation: Specialist - Cloud Service Developer (ABL_SS_600)

Position description:

• The person would be primary responsible for developing solutions using AWS services. Ex: Fargate, Lambda, ECS, ALB, NLB, S3 etc.
• Apply advanced troubleshooting techniques to provide Solutions to issues pertaining to Service Availability, Performance, and Resiliency
• Monitor & Optimize the performance using AWS dashboards and logs
• Partner with Engineering leaders and peers in delivering technology solutions that meet the business requirements 
• Work with the cloud team in agile approach and develop cost optimized solutions

Primary Responsibilities:

• Develop solutions using AWS services includiing Fargate, Lambda, ECS, ALB, NLB, S3 etc.

Reporting Team

• Reporting Designation: Head - Big Data Engineering and Cloud Development (ABL_SS_414)
• Reporting Department: Application Development (2487)

Required Skills:

• AWS certification would be preferred
• Good understanding in Monitoring (Cloudwatch, alarms, logs, custom metrics, Trust SNS configuration)
• Good experience with Fargate, Lambda, ECS, ALB, NLB, S3, Glue, Aurora and other AWS services. 
• Preferred to have Knowledge on Storage (S3, Life cycle management, Event configuration)
• Good in data structure, programming in (pyspark / python / golang / Scala)

1. Sr. Data Engineer:

 Core Skills – Data Engineering, Big Data, Pyspark, Spark SQL and Python

Candidate with prior Palantir Cloud Foundry OR Clinical Trial Data Model background is preferred

Major accountabilities:

• Responsible for Data Engineering, Foundry Data Pipeline Creation, Foundry Analysis & Reporting, Slate Application development, re-usable code development & management and Integrating Internal or External System with Foundry for data ingestion with high quality.
• Have good understanding on Foundry Platform landscape and it’s capabilities
• Performs data analysis required to troubleshoot data related issues and assist in the resolution of data issues.
• Defines company data assets (data models), Pyspark, spark SQL, jobs to populate data models.
• Designs data integrations and data quality framework.
• Design & Implement integration with Internal, External Systems, F1 AWS platform using Foundry Data Connector or Magritte Agent
• Collaboration with data scientists, data analyst and technology teams to document and leverage their understanding of the Foundry integration with different data sources - Actively participate in agile work practices
• Coordinating with Quality Engineer to ensure the all quality controls, naming convention & best practices have been followed

Desired Candidate Profile :

• Strong data engineering background
• Experience with Clinical Data Model is preferred
• Experience in
• SQL Server ,Postgres, Cassandra, Hadoop, and Spark for distributed data storage and parallel computing
• Java and Groovy for our back-end applications and data integration tools
• Python for data processing and analysis
• Cloud infrastructure based on AWS EC2 and S3
• 7+ years IT experience, 2+ years’ experience in Palantir Foundry Platform, 4+ years’ experience in Big Data platform
• 5+ years of Python and Pyspark development experience
• Strong troubleshooting and problem solving skills
• BTech or master's degree in computer science or a related technical field
• Experience designing, building, and maintaining big data pipelines systems
• Hands-on experience on Palantir Foundry Platform and Foundry custom Apps development
• Able to design and implement data integration between Palantir Foundry and external Apps based on Foundry data connector framework
• Hands-on in programming languages primarily Python, R, Java, Unix shell scripts
• Hand-on experience in AWS / Azure cloud platform and stack
• Strong in API based architecture and concept, able to do quick PoC using API integration and development
• Knowledge of machine learning and AI
• Skill and comfort working in a rapidly changing environment with dynamic objectives and iteration with users.

 Demonstrated ability to continuously learn, work independently, and make decisions with minimal supervision

• Should have good hands-on experience in Informatica MDM Customer 360, Data Integration(ETL) using PowerCenter, Data Quality.
• Must have strong skills in Data Analysis, Data Mapping for ETL processes, and Data Modeling.
• Experience with the SIF framework including real-time integration
• Should have experience in building C360 Insights using Informatica
• Should have good experience in creating performant design using Mapplets, Mappings, Workflows for Data Quality(cleansing), ETL.
• Should have experience in building different data warehouse architecture like Enterprise,
• Federated, and Multi-Tier architecture.
• Should have experience in configuring Informatica Data Director in reference to the Data
• Governance of users, IT Managers, and Data Stewards.
• Should have good knowledge in developing complex PL/SQL queries.
• Should have working experience on UNIX and shell scripting to run the Informatica workflows and to control the ETL flow.
• Should know about Informatica Server installation and knowledge on the Administration console.
• Working experience with Developer with Administration is added knowledge.
• Working experience in Amazon Web Services (AWS) is an added advantage. Particularly on AWS S3, Data pipeline, Lambda, Kinesis, DynamoDB, and EMR.
• Should be responsible for the creation of automated BI solutions, including requirements, design,development, testing, and deployment

Intro

Our data and risk team is the core pillar of our business that harnesses alternative data sources to guide the decisions we make at Rely. The team designs, architects, as well as develop and maintain a scalable data platform the powers our machine learning models. Be part of a team that will help millions of consumers across Asia, to be effortlessly in control of their spending and make better decisions.

What will you do
The data engineer is focused on making data correct and accessible, and building scalable systems to access/process it. Another major responsibility is helping AI/ML Engineers write better code.

• Optimize and automate ingestion processes for a variety of data sources such as: click stream, transactional and many other sources.

• Create and maintain optimal data pipeline architecture and ETL processes
• Assemble large, complex data sets that meet functional / non-functional business requirements.
• Develop data pipeline and infrastructure to support real-time decisions
• 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 to assist with data-related technical issues and support their data infrastructure needs.
  
  

What will you need
• 2+ hands-on experience building and implementation of large scale production pipeline and Data Warehouse
• Experience dealing with large scale

• Proficiency in writing and debugging complex SQLs
• Experience working with AWS big data tools
  • Ability to lead the project and implement best data practises and technology

Data Pipelining

• Strong command in building & optimizing data pipelines, architectures and data sets
• Strong command on relational SQL & noSQL databases including Postgres
• Data pipeline and workflow management tools: Azkaban, Luigi, Airflow, etc.

Big Data: Strong experience in big data tools & applications

• Tools: Hadoop, Spark, HDFS etc
• AWS cloud services: EC2, EMR, RDS, Redshift
• Stream-processing systems: Storm, Spark-Streaming, Flink etc.
• Message queuing: RabbitMQ, Spark etc
  
  

Software Development & Debugging

• Strong experience in object-oriented programming/object function scripting languages: Python, Java, C++, Scala, etc
• Strong hold on data structures & algorithms

What would be a bonus

• Prior experience working in a fast-growth Startup
• Prior experience in the payments, fraud, lending, advertising companies dealing with large scale data