11+ Couchbase Jobs in Chennai | Couchbase Job openings in Chennai

 

 

Designation – Deputy Manager - TS

Job Description

1. Total of  8/9 years of development experience Data Engineering . B1/BII role
2. Minimum of 4/5 years in AWS Data Integrations and should be very good on Data modelling skills.
3. Should be very proficient in end to end AWS Data solution design, that not only includes strong data ingestion, integrations (both Data @ rest and Data in Motion) skills but also complete DevOps knowledge.
4. Should have experience in delivering at least 4 Data Warehouse or Data Lake Solutions on AWS.
5. Should be very strong experience on Glue, Lambda, Data Pipeline, Step functions, RDS, CloudFormation etc.
6. Strong Python skill .
7. Should be an expert in Cloud design principles, Performance tuning and cost modelling. AWS certifications will have an added advantage
8. Should be a team player with Excellent communication and should be able to manage his work independently with minimal or no supervision.
9. Life Science & Healthcare domain background will be a plus

Qualifications

BE/Btect/ME/MTech

 

JOB DESCRIPTION:. THE IDEAL CANDIDATE WILL:

• Ensure new features and subject areas are modelled to integrate with existing structures and provide a consistent view. Develop and maintain documentation of the data architecture, data flow and data models of the data warehouse appropriate for various audiences. Provide direction on adoption of Cloud technologies (Snowflake) and industry best practices in the field of data warehouse architecture and modelling.

• Providing technical leadership to large enterprise scale projects. You will also be responsible for preparing estimates and defining technical solutions to proposals (RFPs). This role requires a broad range of skills and the ability to step into different roles depending on the size and scope of the project Roles & Responsibilities.

ELIGIBILITY CRITERIA: Desired Experience/Skills:
• Must have total 5+ yrs. in IT and 2+ years' experience working as a snowflake Data Architect and 4+ years in Data warehouse, ETL, BI projects.
• Must have experience at least two end to end implementation of Snowflake cloud data warehouse and 3 end to end data warehouse implementations on-premise preferably on Oracle.

• Expertise in Snowflake – data modelling, ELT using Snowflake SQL, implementing complex stored Procedures and standard DWH and ETL concepts
• Expertise in Snowflake advanced concepts like setting up resource monitors, RBAC controls, virtual warehouse sizing, query performance tuning, Zero copy clone, time travel and understand how to use these features
• Expertise in deploying Snowflake features such as data sharing, events and lake-house patterns
• Hands-on experience with Snowflake utilities, SnowSQL, SnowPipe, Big Data model techniques using Python
• Experience in Data Migration from RDBMS to Snowflake cloud data warehouse
• Deep understanding of relational as well as NoSQL data stores, methods and approaches (star and snowflake, dimensional modelling)
• Experience with data security and data access controls and design
• Experience with AWS or Azure data storage and management technologies such as S3 and ADLS
• Build processes supporting data transformation, data structures, metadata, dependency and workload management
• Proficiency in RDBMS, complex SQL, PL/SQL, Unix Shell Scripting, performance tuning and troubleshoot
• Provide resolution to an extensive range of complicated data pipeline related problems, proactively and as issues surface
• Must have expertise in AWS or Azure Platform as a Service (PAAS)
• Certified Snowflake cloud data warehouse Architect (Desirable)
• Should be able to troubleshoot problems across infrastructure, platform and application domains.
• Must have experience of Agile development methodologies
• Strong written communication skills. Is effective and persuasive in both written and oral communication

Nice to have Skills/Qualifications:Bachelor's and/or master’s degree in computer science or equivalent experience.
• Strong communication, analytical and problem-solving skills with a high attention to detail.

 

About you:
• You are self-motivated, collaborative, eager to learn, and hands on
• You love trying out new apps, and find yourself coming up with ideas to improve them
• You stay ahead with all the latest trends and technologies
• You are particular about following industry best practices and have high standards regarding quality

• 5+ years of experience in a Data Engineering role on cloud environment

• Must have good experience in Scala/PySpark (preferably on data-bricks environment)

• Extensive experience with Transact-SQL.
• Experience in Data-bricks/Spark.

• Strong experience in Dataware house projects
• Expertise in database development projects with ETL processes.
• Manage and maintain data engineering pipelines

• Develop batch processing, streaming and integration solutions
• Experienced in building and operationalizing large-scale enterprise data solutions and applications

• Using one or more of Azure data and analytics services in combination with custom solutions
• Azure Data Lake, Azure SQL DW (Synapse), and SQL Database products or equivalent products from other cloud services providers

• In-depth understanding of data management (e. g. permissions, security, and monitoring).
• Cloud repositories for e.g. Azure GitHub, Git
• Experience in an agile environment (Prefer Azure DevOps).

Good to have

• Manage source data access security
• Automate Azure Data Factory pipelines
• Continuous Integration/Continuous deployment (CICD) pipelines, Source Repositories
• Experience in implementing and maintaining CICD pipelines
• Power BI understanding, Delta Lake house architecture
• Knowledge of software development best practices.
• Excellent analytical and organization skills.
• Effective working in a team as well as working independently.
• Strong written and verbal communication skills.
• Expertise in database development projects and ETL processes.

Company Description

At Bungee Tech, we help retailers and brands meet customers everywhere and, on every occasion, they are in. We believe that accurate, high-quality data matched with compelling market insights empowers retailers and brands to keep their customers at the center of all innovation and value they are delivering. 

 

We provide a clear and complete omnichannel picture of their competitive landscape to retailers and brands. We collect billions of data points every day and multiple times in a day from publicly available sources. Using high-quality extraction, we uncover detailed information on products or services, which we automatically match, and then proactively track for price, promotion, and availability. Plus, anything we do not match helps to identify a new assortment opportunity.

 

Empowered with this unrivalled intelligence, we unlock compelling analytics and insights that once blended with verified partner data from trusted sources such as Nielsen, paints a complete, consolidated picture of the competitive landscape.

We are looking for a Big Data Engineer who will work on the collecting, storing, processing, and analyzing of huge sets of data. The primary focus will be on choosing optimal solutions to use for these purposes, then maintaining, implementing, and monitoring them.

You will also be responsible for integrating them with the architecture used in the company.

 

We're working on the future. If you are seeking an environment where you can drive innovation, If you want to apply state-of-the-art software technologies to solve real world problems, If you want the satisfaction of providing visible benefit to end-users in an iterative fast paced environment, this is your opportunity.

 

Responsibilities

As an experienced member of the team, in this role, you will:

 

• Contribute to evolving the technical direction of analytical Systems and play a critical role their design and development

 

• You will research, design and code, troubleshoot and support. What you create is also what you own.

 

• Develop the next generation of automation tools for monitoring and measuring data quality, with associated user interfaces.

 

• Be able to broaden your technical skills and work in an environment that thrives on creativity, efficient execution, and product innovation.

 

BASIC QUALIFICATIONS

• Bachelor’s degree or higher in an analytical area such as Computer Science, Physics, Mathematics, Statistics, Engineering or similar.
• 5+ years relevant professional experience in Data Engineering and Business Intelligence
• 5+ years in with Advanced SQL (analytical functions), ETL, Data Warehousing.
• Strong knowledge of data warehousing concepts, including data warehouse technical architectures, infrastructure components, ETL/ ELT and reporting/analytic tools and environments, data structures, data modeling and performance tuning.
• Ability to effectively communicate with both business and technical teams.
• Excellent coding skills in Java, Python, C++, or equivalent object-oriented programming language
• Understanding of relational and non-relational databases and basic SQL
• Proficiency with at least one of these scripting languages: Perl / Python / Ruby / shell script

 

PREFERRED QUALIFICATIONS

 

• Experience with building data pipelines from application databases.
• Experience with AWS services - S3, Redshift, Spectrum, EMR, Glue, Athena, ELK etc.
• Experience working with Data Lakes.
• Experience providing technical leadership and mentor other engineers for the best practices on the data engineering space
• Sharp problem solving skills and ability to resolve ambiguous requirements
• Experience on working with Big Data
• Knowledge and experience on working with Hive and the Hadoop ecosystem
• Knowledge of Spark
• Experience working with Data Science teams

Job Description: Be responsible for scaling our analytics capability across all internal disciplines and guide our strategic direction in regards to analytics Organize and analyze large, diverse data sets across multiple platforms Identify key insights and leverage them to inform and influence product strategy Technical Interactions with vendor or partners in technical capacity for scope/ approach & deliverables. Develops proof of concept to prove or disprove validity of concept. Working with all parts of the business to identify analytical requirements and formalize an approach for reliable, relevant, accurate, efficientreporting on those requirements Designing and implementing advanced statistical testing for customized problem solving Deliver concise verbal and written explanations of analyses to senior management that elevate findings into strategic recommendations Desired Candidate Profile: MTech / BE / BTech / MSc in CS or Stats or Maths, Operation Research, Statistics, Econometrics or in any quantitative field Experience in using Python, R, SAS Experience in working with large data sets and big data systems (SQL, Hadoop, Hive, etc.) Keen aptitude for large-scale data analysis with a passion for identifying key insights from data Expert working knowledge in various machine learning algorithms such XGBoost, SVM Etc. We are looking candidates from the following: Experience in Unsecured Loans & SME Loans analytics (cards, installment loans) - risk based pricing analytics Experience in Differential pricing / selection analytics (retail, airlines / travel etc). Experience in Digital product companies or Digital eCommerce with Product mindset and experience Experience in Fraud / Risk from Banks, NBFC / Fintech / Credit Bureau Experience in Online media with knowledge of media, online ads & sales (agencies) - Knowledge of DMP, DFP, Adobe/Omniture tools, Cloud Experience in Consumer Durable Loans lending companies (Experience in Credit Cards, Personal Loan - optional) Experience in Tractor Loans lending companies (Experience in Farm) Experience in Recovery, Collections analytics Experience in Marketing Analytics with Digital Marketing, Market Mix modelling, Advertising Technology

BRIEF JOB RESPONSIBILITIES:

• Responsible for designing, deploying, and maintaining analytics environment that processes data at scale
• Contribute design, configuration, deployment, and documentation for components that manage data ingestion, real time streaming, batch processing, data extraction, transformation, enrichment, and loading of data into a variety of cloud data platforms, including AWS and Microsoft Azure
• Identify gaps and improve the existing platform to improve quality, robustness, maintainability, and speed
• Evaluate new and upcoming big data solutions and make recommendations for adoption to extend our platform to meet advanced analytics use cases, such as predictive modeling and recommendation engines
• Data Modelling , Data Warehousing on Cloud Scale using Cloud native solutions.
• Perform development, QA, and dev-ops roles as needed to ensure total end to end responsibility of solutions

COMPETENCIES
• Experience building, maintaining, and improving Data Models / Processing Pipeline / routing in large scale environments
• Fluency in common query languages, API development, data transformation, and integration of data streams
• Strong experience with large dataset platforms such as (e.g. Amazon EMR, Amazon Redshift, AWS Lambda & Fargate, Amazon Athena, Azure SQL Database, Azure Database for PostgreSQL, Azure Cosmos DB , Data Bricks)
• Fluency in multiple programming languages, such as Python, Shell Scripting, SQL, Java, or similar languages and tools appropriate for large scale data processing.
• Experience with acquiring data from varied sources such as: API, data queues, flat-file, remote databases
• Understanding of traditional Data Warehouse components (e.g. ETL, Business Intelligence Tools)
• Creativity to go beyond current tools to deliver the best solution to the problem

We are looking for an outstanding Big Data Engineer with experience setting up and maintaining Data Warehouse and Data Lakes for an Organization. This role would closely collaborate with the Data Science team and assist the team build and deploy machine learning and deep learning models on big data analytics platforms.

Roles and Responsibilities:

• Develop and maintain scalable data pipelines and build out new integrations and processes required for optimal extraction, transformation, and loading of data from a wide variety of data sources using 'Big Data' technologies.
• Develop programs in Scala and Python as part of data cleaning and processing.
• Assemble large, complex data sets that meet functional / non-functional business requirements and fostering data-driven decision making across the organization.  
• Responsible to design and develop distributed, high volume, high velocity multi-threaded event processing systems.
• Implement processes and systems to validate data, monitor data quality, ensuring production data is always accurate and available for key stakeholders and business processes that depend on it.
• Perform root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
• Provide high operational excellence guaranteeing high availability and platform stability.
• Closely collaborate with the Data Science team and assist the team build and deploy machine learning and deep learning models on big data analytics platforms.

Skills:

• Experience with Big Data pipeline, Big Data analytics, Data warehousing.
• Experience with SQL/No-SQL, schema design and dimensional data modeling.
• Strong understanding of Hadoop Architecture, HDFS ecosystem and eexperience with Big Data technology stack such as HBase, Hadoop, Hive, MapReduce.
• Experience in designing systems that process structured as well as unstructured data at large scale.
• Experience in AWS/Spark/Java/Scala/Python development.
• Should have Strong skills in PySpark (Python & SPARK). Ability to create, manage and manipulate Spark Dataframes. Expertise in Spark query tuning and performance optimization.
• Experience in developing efficient software code/frameworks for multiple use cases leveraging Python and big data technologies.
• Prior exposure to streaming data sources such as Kafka.
• Should have knowledge on Shell Scripting and Python scripting.
• High proficiency in database skills (e.g., Complex SQL), for data preparation, cleaning, and data wrangling/munging, with the ability to write advanced queries and create stored procedures.
• Experience with NoSQL databases such as Cassandra / MongoDB.
• Solid experience in all phases of Software Development Lifecycle - plan, design, develop, test, release, maintain and support, decommission.
• Experience with DevOps tools (GitHub, Travis CI, and JIRA) and methodologies (Lean, Agile, Scrum, Test Driven Development).
• Experience building and deploying applications on on-premise and cloud-based infrastructure.
• Having a good understanding of machine learning landscape and concepts. 

 

Qualifications and Experience:

Engineering and post graduate candidates, preferably in Computer Science, from premier institutions with proven work experience as a Big Data Engineer or a similar role for 3-5 years.

Certifications:

Good to have at least one of the Certifications listed here:

    AZ 900 - Azure Fundamentals

    DP 200, DP 201, DP 203, AZ 204 - Data Engineering

    AZ 400 - Devops Certification

Looking Data Enginner for our Own organization-

Notice Period- 15-30 days
CTC- upto 15 lpa

 

Preferred Technical Expertise 

1. Expertise in Python programming.
2. Proficient in Pandas/Numpy Libraries. 
3. Experience with Django framework and API Development.
4. Proficient in writing complex queries using SQL
5. Hands on experience with Apache Airflow.
6. Experience with source code versioning tools such as GIT, Bitbucket etc.

 Good to have Skills:

1. Create and maintain Optimal Data Pipeline Architecture
2. Experienced in handling large structured data.
3. Demonstrated ability in solutions covering data ingestion, data cleansing, ETL, Data mart creation and exposing data for consumers.
4. Experience with any cloud platform (GCP is a plus)
5. Experience with JQuery, HTML, Javascript, CSS is a plus.

If Intersted , Kindly share Your CV

Looking for Immediate JoinersAt LatentView, we would expect you to:- Independently handle delivery of analytics assignments- Mentor a team of 3 - 10 people and deliver to exceed client expectations- Co-ordinate with onsite LatentView consultants to ensure high quality, on-time delivery- Take responsibility for technical skill-building within the organization (training, process definition, research of new tools and techniques etc.)You'll be a valuable addition to our team if you have:- 3 - 5 years of hands-on experience in delivering analytics solutions- Great analytical skills, detail-oriented approach- Strong experience in R, SAS, Python, SQL, SPSS, Statistica, MATLAB or such analytic tools would be preferable- Working knowledge in MS Excel, Power Point and data visualization tools like Tableau, etc- Ability to adapt and thrive in the fast-paced environment that young companies operate in- A background in Statistics / Econometrics / Applied Math / Operations Research / MBA, or alternatively an engineering degree from a premier institution.

Software Engineer – ML at Indix provides an opportunity to design and build systems that crunch large amounts of data everyday What We’re Looking For- 3+ years of experience Ability to propose hypothesis and design experiments in the context of specific problems. Should come from a strong engineering background Good overlap with Indix Data tech stack such as Hadoop, MapReduce, HDFS, Spark, Scalding, Scala/Python/C++ Dedication and diligence in understanding the application domain, collecting/cleaning data and conducting experiments. Creativity in model and algorithm development. An obsession to develop algorithms/models that directly impact business. Master’s/Phd. in Computer Science/Statistics is a plus Job Expectations Experience working in text mining and python libraries like scikit-learn, numpy, etc Collect relevant data from production systems/Use crawling and parsing infrastructure to put together data sets. Survey academic literature and identify potential approaches for exploration. Craft, conduct and analyze experiments to evaluate models/algorithms. Communicate findings and take algorithms/models to production with end to end ownership.