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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 

Greetings!!

We are looking out for a technically driven  "Full-Stack Engineer" for one of our premium client

COMPANY DESCRIPTION:

Job ID: ZS070

Hi,

Enterprise minds is looking for Data Scientist. 

Strong in Python,Pyspark.

Prefer immediate joiners

Responsibility

• Partnering with internal business owners (product, marketing, edit, etc.) to understand needs and develop custom analysis to optimize for user engagement and retention
• Good understanding of the underlying business and workings of cross functional teams for successful execution
• Design and develop analyses based on business requirement needs and challenges.
• Leveraging statistical analysis on consumer research and data mining projects, including segmentation, clustering, factor analysis, multivariate regression, predictive modeling, etc.
• Providing statistical analysis on custom research projects and consult on A/B testing and other statistical analysis as needed. Other reports and custom analysis as required.
• Identify and use appropriate investigative and analytical technologies to interpret and verify results.
• Apply and learn a wide variety of tools and languages to achieve results
• Use best practices to develop statistical and/ or machine learning techniques to build models that address business needs.

Requirements

• 2 - 4 years  of relevant experience in Data science.
• Preferred education: Bachelor's degree in a technical field or equivalent experience.
• Experience in advanced analytics, model building, statistical modeling, optimization, and machine learning algorithms.
• Machine Learning Algorithms: Crystal clear understanding, coding, implementation, error analysis, model tuning knowledge on Linear Regression, Logistic Regression, SVM, shallow Neural Networks, clustering, Decision Trees, Random forest, XGBoost, Recommender Systems, ARIMA and Anomaly Detection. Feature selection, hyper parameters tuning, model selection and error analysis, boosting and ensemble methods.
• Strong with programming languages like Python and data processing using SQL or equivalent and ability to experiment with newer open source tools.
• Experience in normalizing data to ensure it is homogeneous and consistently formatted to enable sorting, query and analysis.
• Experience designing, developing, implementing and maintaining a database and programs to manage data analysis efforts.
• Experience with big data and cloud computing viz. Spark, Hadoop (MapReduce, PIG, HIVE).
• Experience in risk and credit score domains preferred.

13+ years of relevant experience with at least 6+ years hands-on coding in the big
data domain.
● Should have experience in architecting data ecosystem for streaming data and
analytical platforms.
● Expert level experience in building fault-tolerant & scalable big-data platforms and
big-data solutions primarily based on the Hadoop ecosystem.
● Expert level experience with Java, Python or Scala programming.
● Expert level experience designing high throughput data services.
● Familiarity with machine learning and AI.
● Experience with Big-Data Technologies (Hive, HBase, Spark, Kafka, Storm,
MapReduce, HDFS, Zookeeper, Scylla, Cassandra, Yarn), understands the
concepts and technology ecosystem around both real-time and batch processing in
Hadoop.
● Strong spoken and written communication skills.
● B.E/B.Tech/MS in Computer Science (or equivalent).
● Effective listening skills and strong collaboration

Key deliverables for the Data Science Engineer would be to help us discover the information hidden in vast amounts of data, and help us make smarter decisions to deliver even better products. Your primary focus will be on applying data mining techniques, doing statistical analysis, and building high-quality prediction systems integrated with our products.

What will you do?

• You will be building and deploying ML models to solve specific business problems related to NLP, computer vision, and fraud detection.
• You will be constantly assessing and improving the model using techniques like Transfer learning
• You will identify valuable data sources and automate collection processes along with undertaking pre-processing of structured and unstructured data
• You will own the complete ML pipeline - data gathering/labeling, cleaning, storage, modeling, training/testing, and deployment.
• Assessing the effectiveness and accuracy of new data sources and data gathering techniques.
• Building predictive models and machine-learning algorithms to apply to data sets.
• Coordinate with different functional teams to implement models and monitor outcomes.
•  
• Presenting information using data visualization techniques and proposing solutions and strategies to business challenges

We would love to hear from you if :

• You have 2+ years of experience as a software engineer at a SaaS or technology company
• Demonstrable hands-on programming experience with Python/R Data Science Stack
• Ability to design and implement workflows of Linear and Logistic Regression, Ensemble Models (Random Forest, Boosting) using R/Python
• Familiarity with Big Data Platforms (Databricks, Hadoop, Hive), AWS Services (AWS, Sagemaker, IAM, S3, Lambda Functions, Redshift, Elasticsearch)
• Experience in Probability and Statistics, ability to use ideas of Data Distributions, Hypothesis Testing and other Statistical Tests.
• Demonstrable competency in Data Visualisation using the Python/R Data Science Stack.
• Preferable Experience Experienced in web crawling and data scraping
• Strong experience in NLP. Worked on libraries such as NLTK, Spacy, Pattern, Gensim etc.
• Experience with text mining, pattern matching and fuzzy matching

Why Tartan?

• Brand new Macbook
• Stock Options
• Health Insurance
• Unlimited Sick Leaves
• Passion Fund (Invest in yourself or your passion project)
• Wind Down

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

 

Responsibilities Description:

Responsible for the development and implementation of machine learning algorithms and techniques to solve business problems and optimize member experiences. Primary duties may include are but not limited to: Design machine learning projects to address specific business problems determined by consultation with business partners. Work with data-sets of varying degrees of size and complexity including both structured and unstructured data. Piping and processing massive data-streams in distributed computing environments such as Hadoop to facilitate analysis. Implements batch and real-time model scoring to drive actions. Develops machine learning algorithms to build customized solutions that go beyond standard industry tools and lead to innovative solutions. Develop sophisticated visualization of analysis output for business users.

 

Experience Requirements:

BS/MA/MS/PhD in Statistics, Computer Science, Mathematics, Machine Learning, Econometrics, Physics, Biostatistics or related Quantitative disciplines. 2-4 years of experience in predictive analytics and advanced expertise with software such as Python, or any combination of education and experience which would provide an equivalent background. Experience in the healthcare sector. Experience in Deep Learning strongly preferred.

 

Required Technical Skill Set:

• Full cycle of building machine learning solutions,

o   Understanding of wide range of algorithms and their corresponding problems to solve

o   Data preparation and analysis

o   Model training and validation

o   Model application to the problem

• Experience using the full open source programming tools and utilities
• Experience in working in end-to-end data science project implementation.
• 2+ years of experience with development and deployment of Machine Learning applications
• 2+ years of experience with NLP approaches in a production setting
• Experience in building models using bagging and boosting algorithms
• Exposure/experience in building Deep Learning models for NLP/Computer Vision use cases preferred
• Ability to write efficient code with good understanding of core Data Structures/algorithms is critical
• Strong python skills following software engineering best practices
• Experience in using code versioning tools like GIT, bit bucket
• Experience in working in Agile projects
• Comfort & familiarity with SQL and Hadoop ecosystem of tools including spark
• Experience managing big data with efficient query program good to have
• Good to have experience in training ML models in tools like Sage Maker, Kubeflow etc.
• Good to have experience in frameworks to depict interpretability of models using libraries like Lime, Shap etc.
• Experience with Health care sector is preferred
• MS/M.Tech or PhD is a plus

• Create and maintain optimal data pipeline architecture
• Assemble large, complex data sets that meet functional / non-functional business requirements.
• Author data services using a variety of programming languages
• Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
• Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using Snowflake Cloud Datawarehouse as well as SQL and Azure ‘big data’ technologies
• Work with stakeholders including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs.
• Keep our data separated and secure across national boundaries through multiple data centers and Azure regions.
• Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader.
• Work with data and analytics experts to strive for greater functionality in our data systems.
• Work in an Agile environment with Scrum teams.
• Ensure data quality and help in achieving data governance.

• 3+ years of experience in a Data Engineer or Software Engineer role
• Undergraduate degree required (Graduate degree preferred) in Computer Science, Statistics, Informatics, Information Systems or another quantitative field.
• Experience using the following software/tools:
• Experience with “Snowflake Cloud Datawarehouse”
• Experience with Azure cloud services: ADLS, ADF, ADLA, AAS
• Experience with data pipeline and workflow management tools
• Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases
• Understanding of Datawarehouse (DWH) systems, and migration from DWH to data lakes/Snowflake
• Understanding of ELT and ETL patterns and when to use each. Understanding of data models and transforming data into the models
• Strong analytic skills related to working with unstructured datasets
• Build processes supporting data transformation, data structures, metadata, dependency and workload management
• Experience supporting and working with cross-functional teams in a dynamic environment.

Hi All,

We are hiring Data Engineer for one of our client for Bangalore & Chennai Location.


Strong Knowledge of SCCM, App V, and Intune infrastructure.

Powershell/VBScript/Python,

Windows Installer

Knowledge of Windows 10 registry

Application Repackaging

Application Sequencing with App-v

Deploying and troubleshooting applications, packages, and Task Sequences.

Security patch deployment and remediation

Windows operating system patching and defender updates

 

Thanks,
Mohan.G

We at artivatic are seeking passionate, talented and research focused natural processing language engineer with strong machine learning and mathematics background to help build industry-leading technology. - The ideal candidate will have research/implementation experience modeling and developing NLP tools and experience working with machine learning/deep learning algorithms.Qualifications :- Bachelors or Master degree in Computer Science, Mathematics or related field with specialization in natural language processing, Machine Learning or Deep Learning.- Publication record in conferences/journals is a plus.- 2+ years of working/research experience building NLP based solutions is preferred.Required Skills :- Hands-on Experience building NLP models using different NLP libraries ad toolkit like NLTK, Stanford NLP etc.- Good understanding of Rule-based, Statistical and probabilistic NLP techniques.- Good knowledge of NLP approaches and concepts like topic modeling, text summarization, semantic modeling, Named Entity recognition etc.- Good understanding of Machine learning and Deep learning algorithms.- Good knowledge of Data Structures and Algorithms.- Strong programming skills in Python/Java/Scala/C/C++.- Strong problem solving and logical skills.- A go-getter kind of attitude with a willingness to learn new technologies.- Well versed with software design paradigms and good development practices.Responsibilities :- Developing novel algorithms and modeling techniques to advance the state of the art in Natural Language Processing.- Developing NLP based tools and solutions end to end.