11+ Amazon VPC Jobs in Delhi, NCR and Gurgaon | Amazon VPC Job openings in Delhi, NCR and Gurgaon

Technical Skills:

• Ability to understand and translate business requirements into design.
• Proficient in AWS infrastructure components such as S3, IAM, VPC, EC2, and Redshift.
• Experience in creating ETL jobs using Python/PySpark.
• Proficiency in creating AWS Lambda functions for event-based jobs.
• Knowledge of automating ETL processes using AWS Step Functions.
• Competence in building data warehouses and loading data into them.

Responsibilities:

• Understand business requirements and translate them into design.
• Assess AWS infrastructure needs for development work.
• Develop ETL jobs using Python/PySpark to meet requirements.
• Implement AWS Lambda for event-based tasks.
• Automate ETL processes using AWS Step Functions.
• Build data warehouses and manage data loading.
• Engage with customers and stakeholders to articulate the benefits of proposed solutions and frameworks.

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

1. Data Engineer

 Required skill set: AWS GLUE, AWS LAMBDA, AWS SNS/SQS, AWS ATHENA, SPARK, SNOWFLAKE, PYTHON

Mandatory Requirements  

• Experience in AWS Glue
• Experience in Apache Parquet 
• Proficient in AWS S3 and data lake 
• Knowledge of Snowflake
• Understanding of file-based ingestion best practices.
• Scripting language - Python & pyspark 

CORE RESPONSIBILITIES 

• Create and manage cloud resources in AWS 
• Data ingestion from different data sources which exposes data using different technologies, such as: RDBMS, REST HTTP API, flat files, Streams, and Time series data based on various proprietary systems. Implement data ingestion and processing with the help of Big Data technologies 
• Data processing/transformation using various technologies such as Spark and Cloud Services. You will need to understand your part of business logic and implement it using the language supported by the base data platform 
• Develop automated data quality check to make sure right data enters the platform and verifying the results of the calculations 
• Develop an infrastructure to collect, transform, combine and publish/distribute customer data.
• Define process improvement opportunities to optimize data collection, insights and displays.
• Ensure data and results are accessible, scalable, efficient, accurate, complete and flexible 
• Identify and interpret trends and patterns from complex data sets 
• Construct a framework utilizing data visualization tools and techniques to present consolidated analytical and actionable results to relevant stakeholders. 
• Key participant in regular Scrum ceremonies with the agile teams  
• Proficient at developing queries, writing reports and presenting findings 
• Mentor junior members and bring best industry practices 

 QUALIFICATIONS 

• 5-7+ years’ experience as data engineer in consumer finance or equivalent industry (consumer loans, collections, servicing, optional product, and insurance sales) 
• Strong background in math, statistics, computer science, data science or related discipline
• Advanced knowledge one of language: Java, Scala, Python, C# 
• Production experience with: HDFS, YARN, Hive, Spark, Kafka, Oozie / Airflow, Amazon Web Services (AWS), Docker / Kubernetes, Snowflake  
• Proficient with
• Data mining/programming tools (e.g. SAS, SQL, R, Python)
• Database technologies (e.g. PostgreSQL, Redshift, Snowflake. and Greenplum)
• Data visualization (e.g. Tableau, Looker, MicroStrategy)
• Comfortable learning about and deploying new technologies and tools. 
• Organizational skills and the ability to handle multiple projects and priorities simultaneously and meet established deadlines. 
• Good written and oral communication skills and ability to present results to non-technical audiences 
• Knowledge of business intelligence and analytical tools, technologies and techniques.

Familiarity and experience in the following is a plus:  

• AWS certification
• Spark Streaming 
• Kafka Streaming / Kafka Connect 
• ELK Stack 
• Cassandra / MongoDB 
• CI/CD: Jenkins, GitLab, Jira, Confluence other related tools

Job Title: Data Engineer

Job Summary: As a Data Engineer, you will be responsible for designing, building, and maintaining the infrastructure and tools necessary for data collection, storage, processing, and analysis. You will work closely with data scientists and analysts to ensure that data is available, accessible, and in a format that can be easily consumed for business insights.

Responsibilities:

• Design, build, and maintain data pipelines to collect, store, and process data from various sources.
• Create and manage data warehousing and data lake solutions.
• Develop and maintain data processing and data integration tools.
• Collaborate with data scientists and analysts to design and implement data models and algorithms for data analysis.
• Optimize and scale existing data infrastructure to ensure it meets the needs of the business.
• Ensure data quality and integrity across all data sources.
• Develop and implement best practices for data governance, security, and privacy.
• Monitor data pipeline performance / Errors and troubleshoot issues as needed.
• Stay up-to-date with emerging data technologies and best practices.

Requirements:

Bachelor's degree in Computer Science, Information Systems, or a related field.

Experience with ETL tools like Matillion,SSIS,Informatica

Experience with SQL and relational databases such as SQL server, MySQL, PostgreSQL, or Oracle.

Experience in writing complex SQL queries

Strong programming skills in languages such as Python, Java, or Scala.

Experience with data modeling, data warehousing, and data integration.

Strong problem-solving skills and ability to work independently.

Excellent communication and collaboration skills.

Familiarity with big data technologies such as Hadoop, Spark, or Kafka.

Familiarity with data warehouse/Data lake technologies like Snowflake or Databricks

Familiarity with cloud computing platforms such as AWS, Azure, or GCP.

Familiarity with Reporting tools

Teamwork/ growth contribution

• Helping the team in taking the Interviews and identifying right candidates
• Adhering to timelines
• Intime status communication and upfront communication of any risks
• Tech, train, share knowledge with peers.
• Good Communication skills
• Proven abilities to take initiative and be innovative
• Analytical mind with a problem-solving aptitude

Good to have :

Master's degree in Computer Science, Information Systems, or a related field.

Experience with NoSQL databases such as MongoDB or Cassandra.

Familiarity with data visualization and business intelligence tools such as Tableau or Power BI.

Knowledge of machine learning and statistical modeling techniques.

If you are passionate about data and want to work with a dynamic team of data scientists and analysts, we encourage you to apply for this position.

Data Scientist

Requirements

● B.Tech/Masters in Mathematics, Statistics, Computer Science or another
quantitative field
● 2-3+ years of work experience in ML domain ( 2-5 years experience )
● Hands-on coding experience in Python
● Experience in machine learning techniques such as Regression, Classification,
Predictive modeling, Clustering, Deep Learning stack, NLP
● Working knowledge of Tensorflow/PyTorch

Optional Add-ons-

● Experience with distributed computing frameworks: Map/Reduce, Hadoop, Spark
etc.
● Experience with databases: MongoDB

• 6+ months of proven experience as a Data Scientist or Data Analyst
• Understanding of machine-learning and operations research
• Extensive knowledge of R, SQL and Excel
• Analytical mind and business acumen
• Strong Statistical understanding
• Problem-solving aptitude
• BSc/BA in Computer Science, Engineering or relevant field; graduate degree in Data Science or other quantitative field is preferred

JD:

Required Skills:

• Intermediate to Expert level hands-on programming using one of programming language- Java or Python or Pyspark or Scala.
• Strong practical knowledge of SQL.
  Hands on experience on Spark/SparkSQL
• Data Structure and Algorithms
• Hands-on experience as an individual contributor in Design, Development, Testing and Deployment of Big Data technologies based applications
• Experience in Big Data application tools, such as Hadoop, MapReduce, Spark, etc
• Experience on NoSQL Databases like HBase, etc
• Experience with Linux OS environment (Shell script, AWK, SED)
• Intermediate RDBMS skill, able to write SQL query with complex relation on top of big RDMS (100+ table)

What you will be doing:

As a part of the Global Credit Risk and Data Analytics team, this person will be responsible for carrying out analytical initiatives which will be as follows: -

• Dive into the data and identify patterns
• Development of end-to-end Credit models and credit policy for our existing credit products
• Leverage alternate data to develop best-in-class underwriting models
• Working on Big Data to develop risk analytical solutions
• Development of Fraud models and fraud rule engine
• Collaborate with various stakeholders (e.g. tech, product) to understand and design best solutions which can be implemented
• Working on cutting-edge techniques e.g. machine learning and deep learning models

Example of projects done in past:

• Lazypay Credit Risk model using CatBoost modelling technique ; end-to-end pipeline for feature engineering and model deployment in production using Python
• Fraud model development, deployment and rules for EMEA region

Basic Requirements:

• 1-3 years of work experience as a Data scientist (in Credit domain)
• 2016 or 2017 batch from a premium college (e.g B.Tech. from IITs, NITs, Economics from DSE/ISI etc)
• Strong problem solving and understand and execute complex analysis
• Experience in at least one of the languages - R/Python/SAS and SQL
• Experience in in Credit industry (Fintech/bank)
• Familiarity with the best practices of Data Science

Add-on Skills : 

• Experience in working with big data
• Solid coding practices
• Passion for building new tools/algorithms
• Experience in developing Machine Learning models