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Senior Big Data Engineer 

Note:   Notice Period : 45 days 

Banyan Data Services (BDS) is a US-based data-focused Company that specializes in comprehensive data solutions and services, headquartered in San Jose, California, USA. 

We are looking for a Senior Hadoop Bigdata Engineer who has expertise in solving complex data problems across a big data platform. You will be a part of our development team based out of Bangalore. This team focuses on the most innovative and emerging data infrastructure software and services to support highly scalable and available infrastructure. 

It's a once-in-a-lifetime opportunity to join our rocket ship startup run by a world-class executive team. We are looking for candidates that aspire to be a part of the cutting-edge solutions and services we offer that address next-gen data evolution challenges. 

Key Qualifications

·   5+ years of experience working with Java and Spring technologies

· At least 3 years of programming experience working with Spark on big data; including experience with data profiling and building transformations

· Knowledge of microservices architecture is plus 

· Experience with any NoSQL databases such as HBase, MongoDB, or Cassandra

· Experience with Kafka or any streaming tools

· Knowledge of Scala would be preferable

· Experience with agile application development 

· Exposure of any Cloud Technologies including containers and Kubernetes 

· Demonstrated experience of performing DevOps for platforms 

· Strong Skillsets in Data Structures & Algorithm in using efficient way of code complexity

· Exposure to Graph databases

· Passion for learning new technologies and the ability to do so quickly 

· A Bachelor's degree in a computer-related field or equivalent professional experience is required

Key Responsibilities

· Scope and deliver solutions with the ability to design solutions independently based on high-level architecture

· Design and develop the big data-focused micro-Services

· Involve in big data infrastructure, distributed systems, data modeling, and query processing

· Build software with cutting-edge technologies on cloud

· Willing to learn new technologies and research-orientated projects 

· Proven interpersonal skills while contributing to team effort by accomplishing related results as needed 

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

1. Big data developer with 8+ years of professional IT experience with expertise in Hadoop ecosystem components in ingestion, Data modeling, querying, processing, storage, analysis, Data Integration and Implementing enterprise level systems spanning Big Data.
2. A skilled developer with strong problem solving, debugging and analytical capabilities, who actively engages in understanding customer requirements.
3. Expertise in Apache Hadoop ecosystem components like Spark, Hadoop Distributed File Systems(HDFS), HiveMapReduce, Hive, Sqoop, HBase, Zookeeper, YARN, Flume, Pig, Nifi, Scala and Oozie.
4. Hands on experience in creating real - time data streaming solutions using Apache Spark core, Spark SQL & DataFrames, Kafka, Spark streaming and Apache Storm.
5. Excellent knowledge of Hadoop architecture and daemons of Hadoop clusters, which include Name node,Data node, Resource manager, Node Manager and Job history server.
6. Worked on both Cloudera and Horton works in Hadoop Distributions. Experience in managing Hadoop clustersusing Cloudera Manager tool.
7. Well versed in installation, Configuration, Managing of Big Data and underlying infrastructure of Hadoop Cluster.
8. Hands on experience in coding MapReduce/Yarn Programs using Java, Scala and Python for analyzing Big Data.
9. Exposure to Cloudera development environment and management using Cloudera Manager.
10. Extensively worked on Spark using Scala on cluster for computational (analytics), installed it on top of Hadoop performed advanced analytical application by making use of Spark with Hive and SQL/Oracle .
11. Implemented Spark using PYTHON and utilizing Data frames and Spark SQL API for faster processing of data and handled importing data from different data sources into HDFS using Sqoop and performing transformations using Hive, MapReduce and then loading data into HDFS.
12. Used Spark Data Frames API over Cloudera platform to perform analytics on Hive data.
13. Hands on experience in MLlib from Spark which are used for predictive intelligence, customer segmentation and for smooth maintenance in Spark streaming.
14. Experience in using Flume to load log files into HDFS and Oozie for workflow design and scheduling.
15. Experience in optimizing MapReduce jobs to use HDFS efficiently by using various compression mechanisms.
16. Working on creating data pipeline for different events of ingestion, aggregation, and load consumer response data into Hive external tables in HDFS location to serve as feed for tableau dashboards.
17. Hands on experience in using Sqoop to import data into HDFS from RDBMS and vice-versa.
18. In-depth Understanding of Oozie to schedule all Hive/Sqoop/HBase jobs.
19. Hands on expertise in real time analytics with Apache Spark.
20. Experience in converting Hive/SQL queries into RDD transformations using Apache Spark, Scala and Python.
21. Extensive experience in working with different ETL tool environments like SSIS, Informatica and reporting tool environments like SQL Server Reporting Services (SSRS).
22. Experience in Microsoft cloud and setting cluster in Amazon EC2 & S3 including the automation of setting & extending the clusters in AWS Amazon cloud.
23. Extensively worked on Spark using Python on cluster for computational (analytics), installed it on top of Hadoop performed advanced analytical application by making use of Spark with Hive and SQL.
24. Strong experience and knowledge of real time data analytics using Spark Streaming, Kafka and Flume.
25. Knowledge in installation, configuration, supporting and managing Hadoop Clusters using Apache, Cloudera (CDH3, CDH4) distributions and on Amazon web services (AWS).
26. Experienced in writing Ad Hoc queries using Cloudera Impala, also used Impala analytical functions.
27. Experience in creating Data frames using PySpark and performing operation on the Data frames using Python.
28. In depth understanding/knowledge of Hadoop Architecture and various components such as HDFS and MapReduce Programming Paradigm, High Availability and YARN architecture.
29. Establishing multiple connections to different Redshift clusters (Bank Prod, Card Prod, SBBDA Cluster) and provide the access for pulling the information we need for analysis. 
30. Generated various kinds of knowledge reports using Power BI based on Business specification. 
31. Developed interactive Tableau dashboards to provide a clear understanding of industry specific KPIs using quick filters and parameters to handle them more efficiently.
32. Well Experience in projects using JIRA, Testing, Maven and Jenkins build tools.
33. Experienced in designing, built, and deploying and utilizing almost all the AWS stack (Including EC2, S3,), focusing on high-availability, fault tolerance, and auto-scaling.
34. Good experience with use-case development, with Software methodologies like Agile and Waterfall.
35. Working knowledge of Amazon's Elastic Cloud Compute( EC2 ) infrastructure for computational tasks and Simple Storage Service ( S3 ) as Storage mechanism.
36. Good working experience in importing data using Sqoop, SFTP from various sources like RDMS, Teradata, Mainframes, Oracle, Netezza to HDFS and performed transformations on it using Hive, Pig and Spark .
37. Extensive experience in Text Analytics, developing different Statistical Machine Learning solutions to various business problems and generating data visualizations using Python and R.
38. Proficient in NoSQL databases including HBase, Cassandra, MongoDB and its integration with Hadoop cluster.
39. Hands on experience in Hadoop Big data technology working on MapReduce, Pig, Hive as Analysis tool, Sqoop and Flume data import/export tools.

Objective

Data Engineer will be responsible for expanding and optimizing our data and database architecture, as well as optimizing data flow and collection for cross functional teams. The ideal candidate is an experienced data pipeline builder and data wrangler who enjoys optimizing data systems and building. The Data Engineer will support our software developers, database architects, data analysts and data scientists on data initiatives and will ensure optimal data delivery architecture is consistent throughout ongoing projects. They must be self-directed and comfortable supporting the data needs of multiple teams, systems, and products

Roles and Responsibilities:

• Should be comfortable in building and optimizing performant data pipelines which include data ingestion, data cleansing and curation into a data warehouse, database, or any other data platform using DASK/Spark.
• Experience in distributed computing environment and Spark/DASK architecture.
• Optimize performance for data access requirements by choosing the appropriate file formats (AVRO, Parquet, ORC etc) and compression codec respectively.
• Experience in writing production ready code in Python and test, participate in code reviews to maintain and improve code quality, stability, and supportability.
• Experience in designing data warehouse/data mart.
• Experience with any RDBMS preferably SQL Server and must be able to write complex SQL queries.
• Expertise in requirement gathering, technical design and functional documents.
• Experience in Agile/Scrum practices.
• Experience in leading other developers and guiding them technically.
• Experience in deploying data pipelines using automated CI/CD approach.
• Ability to write modularized reusable code components.
• Proficient in identifying data issues and anomalies during analysis.
• Strong analytical and logical skills.
• Must be able to comfortably tackle new challenges and learn.
• Must have strong verbal and written communication skills.

Required skills:

• Knowledge on GCP
• Expertise in Google BigQuery
• Expertise in Airflow
• Good Hands on SQL
• Data warehousing concepts

About Kloud9:

Kloud9 exists with the sole purpose of providing cloud expertise to the retail industry. Our team of cloud architects, engineers and developers help retailers launch a successful cloud initiative so you can quickly realise the benefits of cloud technology. Our standardised, proven cloud adoption methodologies reduce the cloud adoption time and effort so you can directly benefit from lower migration costs.

Kloud9 was founded with the vision of bridging the gap between E-commerce and cloud. The E-commerce of any industry is limiting and poses a huge challenge in terms of the finances spent on physical data structures.

At Kloud9, we know migrating to the cloud is the single most significant technology shift your company faces today. We are your trusted advisors in transformation and are determined to build a deep partnership along the way. Our cloud and retail experts will ease your transition to the cloud.

Our sole focus is to provide cloud expertise to retail industry giving our clients the empowerment that will take their business to the next level. Our team of proficient architects, engineers and developers have been designing, building and implementing solutions for retailers for an average of more than 20 years.

We are a cloud vendor that is both platform and technology independent. Our vendor independence not just provides us with a unique perspective into the cloud market but also ensures that we deliver the cloud solutions available that best meet our clients' requirements.

●    Overall 8+ Years of Experience in Web Application development.

●    5+ Years of development experience with JAVA8 , Springboot, Microservices and middleware

●    3+ Years of Designing Middleware using Node JS platform.

●    good to have 2+ Years of Experience in using NodeJS along with AWS Serverless platform.

●    Good Experience with Javascript / TypeScript, Event Loops, ExpressJS, GraphQL, SQL DB (MySQLDB), NoSQL DB(MongoDB) and YAML templates.

●    Good Experience with TDD Driven Development and Automated Unit Testing.

●    Good Experience with exposing and consuming Rest APIs in Java 8, Springboot platform and Swagger API contracts.

●    Good Experience in building NodeJS middleware performing Transformations, Routing, Aggregation, Orchestration and Authentication(JWT/OAUTH).

●    Experience supporting and working with cross-functional teams in a dynamic environment.

●    Experience working in Agile Scrum Methodology.

●    Very good Problem-Solving Skills.

●    Very good learner and passion for technology.

●     Excellent verbal and written communication skills in English

●     Ability to communicate effectively with team members and business stakeholders

Secondary Skill Requirements:

● Experience working with any of Loopback, NestJS, Hapi.JS, Sails.JS, Passport.JS

Why Explore a Career at Kloud9:

With job opportunities in prime locations of US, London, Poland and Bengaluru, we help build your career paths in cutting edge technologies of AI, Machine Learning and Data Science. Be part of an inclusive and diverse workforce that's changing the face of retail technology with their creativity and innovative solutions. Our vested interest in our employees translates to deliver the best products and solutions to our customers.

JD for IOT DE:

The role requires experience in Azure core technologies – IoT Hub/ Event Hub, Stream Analytics, IoT Central, Azure Data Lake Storage, Azure Cosmos, Azure Data Factory, Azure SQL Database, Azure HDInsight / Databricks, SQL data warehouse.

You Have:

• Minimum 2 years of software development experience
• Minimum 2 years of experience in IoT/streaming data pipelines solution development
• Bachelor's and/or Master’s degree in computer science
• Strong Consulting skills in data management including data governance, data quality, security, data integration, processing, and provisioning
• Delivered data management projects with real-time/near real-time data insights delivery on Azure Cloud
• Translated complex analytical requirements into the technical design including data models, ETLs, and Dashboards / Reports
• Experience deploying dashboards and self-service analytics solutions on both relational and non-relational databases
• Experience with different computing paradigms in databases such as In-Memory, Distributed, Massively Parallel Processing
• Successfully delivered large scale IOT data management initiatives covering Plan, Design, Build and Deploy phases leveraging different delivery methodologies including Agile
• Experience in handling telemetry data with Spark Streaming, Kafka, Flink, Scala, Pyspark, Spark SQL.
• Hands-on experience on containers and Dockers
• Exposure to streaming protocols like MQTT and AMQP
• Knowledge of OT network protocols like OPC UA, CAN Bus, and similar protocols
• Strong knowledge of continuous integration, static code analysis, and test-driven development
• Experience in delivering projects in a highly collaborative delivery model with teams at onsite and offshore
• Must have excellent analytical and problem-solving skills
• Delivered change management initiatives focused on driving data platforms adoption across the enterprise
• Strong verbal and written communications skills are a must, as well as the ability to work effectively across internal and external organizations
   

Roles & Responsibilities
 

You Will:

• Translate functional requirements into technical design
• Interact with clients and internal stakeholders to understand the data and platform requirements in detail and determine core Azure services needed to fulfill the technical design
• Design, Develop and Deliver data integration interfaces in ADF and Azure Databricks
• Design, Develop and Deliver data provisioning interfaces to fulfill consumption needs
• Deliver data models on Azure platform, it could be on Azure Cosmos, SQL DW / Synapse, or SQL
• Advise clients on ML Engineering and deploying ML Ops at Scale on AKS
• Automate core activities to minimize the delivery lead times and improve the overall quality
• Optimize platform cost by selecting the right platform services and architecting the solution in a cost-effective manner
• Deploy Azure DevOps and CI CD processes
• Deploy logging and monitoring across the different integration points for critical alerts

• Expertise in designing and implementing enterprise scale database (OLTP) and Data warehouse solutions.
• Hands on experience in implementing Azure SQL Database, Azure SQL Date warehouse (Azure Synapse Analytics) and big data processing using Azure Databricks and Azure HD Insight.
• Expert in writing T-SQL programming for complex stored procedures, functions, views and query optimization.
• Should be aware of Database development for both on-premise and SAAS Applications using SQL Server and PostgreSQL.
• Experience in ETL and ELT implementations using Azure Data Factory V2 and SSIS.
• Experience and expertise in building machine learning models using Logistic and linear regression, Decision tree  and Random forest Algorithms.
• PolyBase queries for exporting and importing data into Azure Data Lake.
• Building data models both tabular and multidimensional using SQL Server data tools.
• Writing data preparation, cleaning and processing steps using Python, SCALA, and R.
• Programming experience using python libraries NumPy, Pandas and Matplotlib.
• Implementing NOSQL databases and writing queries using cypher.
• Designing end user visualizations using Power BI, QlikView and Tableau.
• Experience working with all versions of SQL Server 2005/2008/2008R2/2012/2014/2016/2017/2019
• Experience using the expression languages MDX and DAX.
• Experience in migrating on-premise SQL server database to Microsoft Azure.
• Hands on experience in using Azure blob storage, Azure Data Lake Storage Gen1 and Azure Data Lake Storage Gen2.
• Performance tuning complex SQL queries, hands on experience using SQL Extended events.
• Data modeling using Power BI for Adhoc reporting.
• Raw data load automation using T-SQL and SSIS
• Expert in migrating existing on-premise database to SQL Azure.
• Experience in using U-SQL for Azure Data Lake Analytics.
• Hands on experience in generating SSRS reports using MDX.
• Experience in designing predictive models using Python and SQL Server.
• Developing machine learning models using Azure Databricks and SQL Server