Senior Data Engineer

Publicis Sapient Overview:

The Senior Associate People Senior Associate L1 in Data Engineering, you will translate client requirements into technical design, and implement components for data engineering solution. Utilize deep understanding of data integration and big data design principles in creating custom solutions or implementing package solutions. You will independently drive design discussions to insure the necessary health of the overall solution 

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Job Summary:

As Senior Associate L2 in Data Engineering, you will translate client requirements into technical design, and implement components for data engineering solution. Utilize deep understanding of data integration and big data design principles in creating custom solutions or implementing package solutions. You will independently drive design discussions to insure the necessary health of the overall solution

The role requires a hands-on technologist who has strong programming background like Java / Scala / Python, should have experience in Data Ingestion, Integration and data Wrangling, Computation, Analytics pipelines and exposure to Hadoop ecosystem components. You are also required to have hands-on knowledge on at least one of AWS, GCP, Azure cloud platforms.

Role & Responsibilities:

Your role is focused on Design, Development and delivery of solutions involving:

• Data Integration, Processing & Governance

• Data Storage and Computation Frameworks, Performance Optimizations

• Analytics & Visualizations

• Infrastructure & Cloud Computing

• Data Management Platforms

• Implement scalable architectural models for data processing and storage

• Build functionality for data ingestion from multiple heterogeneous sources in batch & real-time mode

• Build functionality for data analytics, search and aggregation

Experience Guidelines:

Mandatory Experience and Competencies:

# Competency

1.Overall 5+ years of IT experience with 3+ years in Data related technologies

2.Minimum 2.5 years of experience in Big Data technologies and working exposure in at least one cloud platform on related data services (AWS / Azure / GCP)

3.Hands-on experience with the Hadoop stack – HDFS, sqoop, kafka, Pulsar, NiFi, Spark, Spark Streaming, Flink, Storm, hive, oozie, airflow and other components required in building end to end data pipeline.

4.Strong experience in at least of the programming language Java, Scala, Python. Java preferable

5.Hands-on working knowledge of NoSQL and MPP data platforms like Hbase, MongoDb, Cassandra, AWS Redshift, Azure SQLDW, GCP BigQuery etc

6.Well-versed and working knowledge with data platform related services on at least 1 cloud platform, IAM and data security

Preferred Experience and Knowledge (Good to Have):

# Competency

1.Good knowledge of traditional ETL tools (Informatica, Talend, etc) and database technologies (Oracle, MySQL, SQL Server, Postgres) with hands on experience

2.Knowledge on data governance processes (security, lineage, catalog) and tools like Collibra, Alation etc

3.Knowledge on distributed messaging frameworks like ActiveMQ / RabbiMQ / Solace, search & indexing and Micro services architectures

4.Performance tuning and optimization of data pipelines

5.CI/CD – Infra provisioning on cloud, auto build & deployment pipelines, code quality

6.Cloud data specialty and other related Big data technology certifications

Personal Attributes:

• Strong written and verbal communication skills

• Articulation skills

• Good team player

• Self-starter who requires minimal oversight

• Ability to prioritize and manage multiple tasks

• Process orientation and the ability to define and set up processes

• Bring in industry best practices around creating and maintaining robust data pipelines for complex data projects with/without AI component
  • programmatically ingesting data from several static and real-time sources (incl. web scraping)
  • rendering results through dynamic interfaces incl. web / mobile / dashboard with the ability to log usage and granular user feedbacks
  • performance tuning and optimal implementation of complex Python scripts (using SPARK), SQL (using stored procedures, HIVE), and NoSQL queries in a production environment

• Industrialize ML / DL solutions and deploy and manage production services; proactively handle data issues arising on live apps
• Perform ETL on large and complex datasets for AI applications - work closely with data scientists on performance optimization of large-scale ML/DL model training
• Build data tools to facilitate fast data cleaning and statistical analysis
• Ensure data architecture is secure and compliant
• Resolve issues escalated from Business and Functional areas on data quality, accuracy, and availability
• Work closely with APAC CDO and coordinate with a fully decentralized team across different locations in APAC and global HQ (Paris).

•  Expert in structured and unstructured data in traditional and Big data environments – Oracle / SQLserver, MongoDB, Hive / Pig, BigQuery, and Spark
• Have excellent knowledge of Python programming both in traditional and distributed models (PySpark)
• Expert in shell scripting and writing schedulers
• Hands-on experience with Cloud - deploying complex data solutions in hybrid cloud / on-premise environment both for data extraction/storage and computation
• Hands-on experience in deploying production apps using large volumes of data with state-of-the-art technologies like Dockers, Kubernetes, and Kafka
• Strong knowledge of data security best practices
• 5+ years experience in a data engineering role
• Science / Engineering graduate from a Tier-1 university in the country
• And most importantly, you must be a passionate coder who really cares about building apps that can help people do things better, smarter, and faster even when they sleep

Location:  Chennai
Education: BE/BTech
Experience: Minimum 3+ years of experience as a Data Scientist/Data Engineer

Domain knowledge: Data cleaning, modelling, analytics, statistics, machine learning, AI

Requirements:

• To be part of Digital Manufacturing and Industrie 4.0 projects across client group of companies
• Design and develop AI//ML models to be deployed across factories
• Knowledge on Hadoop, Apache Spark, MapReduce, Scala, Python programming, SQL and NoSQL databases is required
• Should be strong in statistics, data analysis, data modelling, machine learning techniques and Neural Networks
• Prior experience in developing AI and ML models is required
• Experience with data from the Manufacturing Industry would be a plus

Roles and Responsibilities:

• Develop AI and ML models for the Manufacturing Industry with a focus on Energy, Asset Performance Optimization and Logistics
• Multitasking, good communication necessary
• Entrepreneurial attitude

• Job Location:                      Chennai
• Reporting to:                      Team Leader, Energy Management System

Company Overview:

Rakuten, Inc. (TSE's first section: 4755) is the largest ecommerce company in Japan, and third largest eCommerce marketplace company worldwide. Rakuten provides a variety of consumer and business-focused services including e-commerce, e-reading, travel, banking, securities, credit card, e-money, portal and media, online marketing and professional sports. The company is expanding globally and currently has operations throughout Asia, Western Europe, and the Americas. Founded in 1997, Rakuten is headquartered in Tokyo, with over 17,000 employees and partner staff worldwide. Rakuten's 2018 revenues were 1101.48 billions yen. 　 -In Japanese, Rakuten stands for ‘optimism.’ -It means we believe in the future. -It’s an understanding that, with the right mind-set, -we can make the future better by what we do today. Today, our 70+ businesses span e-commerce, digital content, communications and FinTech, bringing the joy of discovery to more than 1.2 billion members across the world.

Website : https://www.rakuten.com/">https://www.rakuten.com/

Crunchbase : https://www.crunchbase.com/organization/rakuten">Rakuten has raised a total of https://www.crunchbase.com/search/funding_rounds/field/organizations/funding_total/rakuten">$42.4M in funding over https://www.crunchbase.com/search/funding_rounds/field/organizations/num_funding_rounds/rakuten">2 rounds

Companysize : 10,001 + Employees

Founded : 1997

Headquarters : Tokyo, Japan

Work location : Bangalore (M.G.Road)

Please find below Job Description.

Role Description – Data Engineer for AN group (Location - India)

Key responsibilities include:

We are looking for engineering candidate in our Autonomous Networking Team. The ideal candidate must have following abilities –

• Hands- on experience in big data computation technologies (at least one and potentially several of the following: Spark and Spark Streaming, Hadoop, Storm, Kafka Streaming, Flink, etc)
• Familiar with other related big data technologies, such as big data storage technologies (e.g., Phoenix/HBase, Redshift, Presto/Athena, Hive, Spark SQL, BigTable, BigQuery, Clickhouse, etc), messaging layer (Kafka, Kinesis, etc), Cloud and container- based deployments (Docker, Kubernetes etc), Scala, Akka, SocketIO, ElasticSearch, RabbitMQ, Redis, Couchbase, JAVA, Go lang.
• Partner with product management and delivery teams to align and prioritize current and future new product development initiatives in support of our business objectives
• Work with cross functional engineering teams including QA, Platform Delivery and DevOps
• Evaluate current state solutions to identify areas to improve standards, simplify, and enhance functionality and/or transition to effective solutions to improve supportability and time to market
• Not afraid of refactoring existing system and guiding the team about same.
• Experience with Event driven Architecture, Complex Event Processing
• Extensive experience building and owning large- scale distributed backend systems.

Skills- Informatica with Big Data Management

1.Minimum 6 to 8 years of experience in informatica BDM development
2.Experience working on Spark/SQL
3.Develops informtica mapping/Sql 

Responsibilities:

• Exploring and visualizing data to gain an understanding of it, then identifying differences in data distribution that could affect performance when deploying the model in the real world.
• Verifying data quality, and/or ensuring it via data cleaning.
• Able to adapt and work fast in producing the output which upgrades the decision making of stakeholders using ML.
• To design and develop Machine Learning systems and schemes. 
• To perform statistical analysis and fine-tune models using test results.
• To train and retrain ML systems and models as and when necessary. 
• To deploy ML models in production and maintain the cost of cloud infrastructure.
• To develop Machine Learning apps according to client and data scientist requirements.
• To analyze the problem-solving capabilities and use-cases of ML algorithms and rank them by how successful they are in meeting the objective.

Technical Knowledge:

• Worked with real time problems, solved them using ML and deep learning models deployed in real time and should have some awesome projects under his belt to showcase. 
• Proficiency in Python and experience with working with Jupyter Framework, Google collab and cloud hosted notebooks such as AWS sagemaker, DataBricks etc.
• Proficiency in working with libraries Sklearn, Tensorflow, Open CV2, Pyspark,  Pandas, Numpy and related libraries.
• Expert in visualising and manipulating complex datasets.
• Proficiency in working with visualisation libraries such as seaborn, plotly, matplotlib etc.
• Proficiency in Linear Algebra, statistics and probability required for Machine Learning.
• Proficiency in ML Based algorithms for example, Gradient boosting, stacked Machine learning, classification algorithms and deep learning algorithms. Need to have experience in hypertuning various models and comparing the results of algorithm performance.
• Big data Technologies such as Hadoop stack and Spark. 
• Basic use of clouds (VM’s example EC2).
• Brownie points for Kubernetes and Task Queues.      
• Strong written and verbal communications.
• Experience working in an Agile environment.

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