Principal Engineer - Java+Scala+AWS

LogiNext is looking for a technically savvy and passionate Senior Software Engineer - Data Science to analyze large amounts of raw information to find patterns that will help improve our company. We will rely on you to build data products to extract valuable business insights.

In this role, you should be highly analytical with a knack for analysis, math and statistics. Critical thinking and problem-solving skills are essential for interpreting data. We also want to see a passion for machine-learning and research.

Your goal will be to help our company analyze trends to make better decisions. Without knowledge of how the software works, data scientists might have difficulty in work. Apart from experience in developing R and Python, they must know modern approaches to software development and their impact. DevOps continuous integration and deployment, experience in cloud computing are everyday skills to manage and process data.

Responsibilities :

Adapting and enhancing machine learning techniques based on physical intuition about the domain Design sampling methodology, prepare data, including data cleaning, univariate analysis, missing value imputation, , identify appropriate analytic and statistical methodology, develop predictive models and document process and results Lead projects both as a principal investigator and project manager, responsible for meeting project requirements on schedule and on budget Coordinate and lead efforts to innovate by deriving insights from heterogeneous sets of data generated by our suite of Aerospace products Support and mentor data scientists Maintain and work with our data pipeline that transfers and processes several terabytes of data using Spark, Scala, Python, Apache Kafka, Pig/Hive & Impala Work directly with application teams/partners (internal clients such as Xbox, Skype, Office) to understand their offerings/domain and help them become successful with data so they can run controlled experiments (a/b testing) Understand the data generated by experiments, and producing actionable, trustworthy conclusions from them Apply data analysis, data mining and data processing to present data clearly and develop experiments (ab testing) Work with development team to build tools for data logging and repeatable data tasks tol accelerate and automate data scientist duties

Requirements:

Bachelor’s or Master’s degree in Computer Science, Math, Physics, Engineering, Statistics or other technical field. PhD preferred 4 to 7 years of experience in data mining, data modeling, and reporting 3+ years of experience working with large data sets or do large scale quantitative analysis Expert SQL scripting required Development experience in one of the following: Scala, Java, Python, Perl, PHP, C++ or C# Experience working with Hadoop, Pig/Hive, Spark, MapReduce Ability to drive projects Basic understanding of statistics – hypothesis testing, p-values, confidence intervals, regression, classification, and optimization are core lingo Analysis - Should be able to perform Exploratory Data Analysis and get actionable insights from the data, with impressive visualization. Modeling - Should be familiar with ML concepts and algorithms; understanding of the internals and pros/cons of models is required. Strong algorithmic problem-solving skills Experience manipulating large data sets through statistical software (ex. R, SAS) or other methods Superior verbal, visual and written communication skills to educate and work with cross functional teams on controlled experiments Experimentation design or A/B testing experience is preferred. Experince in team management.

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 L1 in Data Engineering, you will do 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. Having hands-on knowledge on at least one of AWS, GCP, Azure cloud platforms will be preferable.

Role & Responsibilities:

Job Title: Senior Associate L1 – Data Engineering

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

• Data Ingestion, Integration and Transformation

• Data Storage and Computation Frameworks, Performance Optimizations

• Analytics & Visualizations

• Infrastructure & Cloud Computing

• Data Management Platforms

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

• Build functionality for data analytics, search and aggregation

Experience Guidelines:

Mandatory Experience and Competencies:

# Competency

1.Overall 3.5+ years of IT experience with 1.5+ years in Data related technologies

2.Minimum 1.5 years of experience in Big Data technologies

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. Working knowledge on real-time data pipelines is added advantage.

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

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.Working knowledge with data platform related services on at least 1 cloud platform, IAM and data security

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

Job Title: Senior Associate L1 – Data Engineering

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

Daily and monthly responsibilities

• Review and coordinate with business application teams on data delivery requirements.
• Develop estimation and proposed delivery schedules in coordination with development team.
• Develop sourcing and data delivery designs.
• Review data model, metadata and delivery criteria for solution.
• Review and coordinate with team on test criteria and performance of testing.
• Contribute to the design, development and completion of project deliverables.
• Complete in-depth data analysis and contribution to strategic efforts
• Complete understanding of how we manage data with focus on improvement of how data is sourced and managed across multiple business areas.

Basic Qualifications

• Bachelor’s degree.
• 5+ years of data analysis working with business data initiatives.
• Knowledge of Structured Query Language (SQL) and use in data access and analysis.
• Proficient in data management including data analytical capability.
• Excellent verbal and written communications also high attention to detail.
• Experience with Python.
• Presentation skills in demonstrating system design and data analysis solutions.

This profile will include the following responsibilities:

- Develop Parsers for XML and JSON Data sources/feeds

- Write Automation Scripts for product development

- Build API Integrations for 3^rd Party product integration

- Perform Data Analysis

- Research on Machine learning algorithms

- Understand AWS cloud architecture and work with 3 party vendors for deployments

Role: Data Engineer  
Company: PayU

Location: Bangalore/ Mumbai

Experience : 2-5 yrs

About Company:

PayU is the payments and fintech business of Prosus, a global consumer internet group and one of the largest technology investors in the world. Operating and investing globally in markets with long-term growth potential, Prosus builds leading consumer internet companies that empower people and enrich communities.

The leading online payment service provider in 36 countries, PayU is dedicated to creating a fast, simple and efficient payment process for merchants and buyers. Focused on empowering people through financial services and creating a world without financial borders where everyone can prosper, PayU is one of the biggest investors in the fintech space globally, with investments totalling $700 million- to date. PayU also specializes in credit products and services for emerging markets across the globe. We are dedicated to removing risks to merchants, allowing consumers to use credit in ways that suit them and enabling a greater number of global citizens to access credit services.

Our local operations in Asia, Central and Eastern Europe, Latin America, the Middle East, Africa and South East Asia enable us to combine the expertise of high growth companies with our own unique local knowledge and technology to ensure that our customers have access to the best financial services.

India is the biggest market for PayU globally and the company has already invested $400 million in this region in last 4 years. PayU in its next phase of growth is developing a full regional fintech ecosystem providing multiple digital financial services in one integrated experience. We are going to do this through 3 mechanisms: build, co-build/partner; select strategic investments. 

PayU supports over 350,000+ merchants and millions of consumers making payments online with over 250 payment methods and 1,800+ payment specialists. The markets in which PayU operates represent a potential consumer base of nearly 2.3 billion people and a huge growth potential for merchants. 

Job responsibilities:

• Design infrastructure for data, especially for but not limited to consumption in machine learning applications 
• Define database architecture needed to combine and link data, and ensure integrity across different sources 
• Ensure performance of data systems for machine learning to customer-facing web and mobile applications using cutting-edge open source frameworks, to highly available RESTful services, to back-end Java based systems 
• Work with large, fast, complex data sets to solve difficult, non-routine analysis problems, applying advanced data handling techniques if needed 
• Build data pipelines, includes implementing, testing, and maintaining infrastructural components related to the data engineering stack.
• Work closely with Data Engineers, ML Engineers and SREs to gather data engineering requirements to prototype, develop, validate and deploy data science and machine learning solutions

Requirements to be successful in this role: 

• Strong knowledge and experience in Python, Pandas, Data wrangling, ETL processes, statistics, data visualisation, Data Modelling and Informatica.
• Strong experience with scalable compute solutions such as in Kafka, Snowflake
• Strong experience with workflow management libraries and tools such as Airflow, AWS Step Functions etc. 
• Strong experience with data engineering practices (i.e. data ingestion pipelines and ETL) 
• A good understanding of machine learning methods, algorithms, pipelines, testing practices and frameworks 
• Preferred) MEng/MSc/PhD degree in computer science, engineering, mathematics, physics, or equivalent (preference: DS/ AI) 
• Experience with designing and implementing tools that support sharing of data, code, practices across organizations at scale 

• 4-10 years of experience in software development.
• At least 2 years of relevant work experience on large scale Data applications.
• Strong coding experience in Java is mandatory
• Good aptitude, strong problem solving abilities, and analytical skills, ability to take ownership as appropriate
• Should be able to do coding, debugging, performance tuning and deploying the apps to Prod.
• Should have good working experience on
• o Hadoop ecosystem (HDFS, Hive, Yarn, File formats like Avro/Parquet)
• o Kafka
• o J2EE Frameworks (Spring/Hibernate/REST)
• o Spark Streaming or any other streaming technology.
• Strong coding experience in Java is mandatory
• Ability to work on the sprint stories to completion along with Unit test case coverage.
• Experience working in Agile Methodology
• Excellent communication and coordination skills
• Knowledgeable (and preferred hands on) - UNIX environments, different continuous integration tools.
• Must be able to integrate quickly into the team and work independently towards team goals

• Take the complete responsibility of the sprint stories' execution
• Be accountable for the delivery of the tasks in the defined timelines with good quality.
• Follow the processes for project execution and delivery.
• Follow agile methodology
• Work with the team lead closely and contribute to the smooth delivery of the project.
• Understand/define the architecture and discuss the pros-cons of the same with the team
• Involve in the brainstorming sessions and suggest improvements in the architecture/design.
• Work with other team leads to get the architecture/design reviewed.
• Work with the clients and counter-parts (in US) of the project.
• Keep all the stakeholders updated about the project/task status/risks/issues if there are any.