Bigdata Engineer

Mandatory Skills: Azure Data Lake Storage, Azure SQL databases, Azure Synapse, Data Bricks (Pyspark/Spark), Python, SQL, Azure Data Factory.

Good to have: Power BI, Azure IAAS services, Azure Devops, Microsoft Fabric

Ø Very strong understanding on ETL and ELT

Ø Very strong understanding on Lakehouse architecture.

Ø Very strong knowledge in Pyspark and Spark architecture.

Ø Good knowledge in Azure data lake architecture and access controls

Ø Good knowledge in Microsoft Fabric architecture

Ø Good knowledge in Azure SQL databases

Ø Good knowledge in T-SQL

Ø Good knowledge in CI /CD process using Azure devops

Ø Power BI

Job Description

1. Solid technical skills with a proven and successful history working with data at scale and empowering organizations through data
2. Big data processing frameworks: Spark, Scala, Hadoop, Hive, Kafka, EMR with Python
3. Advanced experience and hands-on architecture and administration experience on big data platforms

We are looking for a Big Data Engineer with java for Chennai Location

Location : Chennai 

Exp : 11 to 15 Years 

Job description

Required Skill:

1. Candidate should have minimum 7 years of experience as total

2. Candidate should have minimum 4 years of experience in Big Data design and development

3. Candidate should have experience in Java, Spark, Hive & Hadoop, Python 

4. Candidate should have experience in any RDBMS.

Roles & Responsibility:

1. To create work plans, monitor and track the work schedule for on time delivery as per the defined quality standards.

2. To develop and guide the team members in enhancing their technical capabilities and increasing productivity.

3. To ensure process improvement and compliance in the assigned module, and participate in technical discussions or review.

4. To prepare and submit status reports for minimizing exposure and risks on the project or closure of escalation

Regards,

Priyanka S

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Roles and

Responsibilities

Seeking AWS Cloud Engineer /Data Warehouse Developer for our Data CoE team to

help us in configure and develop new AWS environments for our Enterprise Data Lake,

migrate the on-premise traditional workloads to cloud. Must have a sound

understanding of BI best practices, relational structures, dimensional data modelling,

structured query language (SQL) skills, data warehouse and reporting techniques.

 Extensive experience in providing AWS Cloud solutions to various business

use cases.

 Creating star schema data models, performing ETLs and validating results with

business representatives

 Supporting implemented BI solutions by: monitoring and tuning queries and

data loads, addressing user questions concerning data integrity, monitoring

performance and communicating functional and technical issues.

Job Description: -

This position is responsible for the successful delivery of business intelligence

information to the entire organization and is experienced in BI development and

implementations, data architecture and data warehousing.

Requisite Qualification

Essential

-

AWS Certified Database Specialty or -

AWS Certified Data Analytics

Preferred

Any other Data Engineer Certification

Requisite Experience

Essential 4 -7 yrs of experience

Preferred 2+ yrs of experience in ETL & data pipelines

Skills Required

Special Skills Required

 AWS: S3, DMS, Redshift, EC2, VPC, Lambda, Delta Lake, CloudWatch etc.

 Bigdata: Databricks, Spark, Glue and Athena

 Expertise in Lake Formation, Python programming, Spark, Shell scripting

 Minimum Bachelor’s degree with 5+ years of experience in designing, building,

and maintaining AWS data components

 3+ years of experience in data component configuration, related roles and

access setup

 Expertise in Python programming

 Knowledge in all aspects of DevOps (source control, continuous integration,

deployments, etc.)

 Comfortable working with DevOps: Jenkins, Bitbucket, CI/CD

 Hands on ETL development experience, preferably using or SSIS

 SQL Server experience required

 Strong analytical skills to solve and model complex business requirements

 Sound understanding of BI Best Practices/Methodologies, relational structures,

dimensional data modelling, structured query language (SQL) skills, data

warehouse and reporting techniques

Preferred Skills

Required

 Experience working in the SCRUM Environment.

 Experience in Administration (Windows/Unix/Network/Database/Hadoop) is a

plus.

 Experience in SQL Server, SSIS, SSAS, SSRS

 Comfortable with creating data models and visualization using Power BI

 Hands on experience in relational and multi-dimensional data modelling,

including multiple source systems from databases and flat files, and the use of

standard data modelling tools

 Ability to collaborate on a team with infrastructure, BI report development and

business analyst resources, and clearly communicate solutions to both

technical and non-technical team members

About RARA NOW :

• RaRa Now is revolutionizing instant delivery for e-commerce in Indonesia through data-driven logistics.

• RaRa Now is making instant and same-day deliveries scalable and cost-effective by leveraging a differentiated operating model and real-time optimization technology. RaRa makes it possible for anyone, anywhere to get same-day delivery in Indonesia. While others are focusing on - one-to-one- deliveries, the company has developed proprietary, real-time batching tech to do - many-to-many- deliveries within a few hours. RaRa is already in partnership with some of the top eCommerce players in Indonesia like Blibli, Sayurbox, Kopi Kenangan, and many more.

• We are a distributed team with the company headquartered in Singapore, core operations in Indonesia, and a technology team based out of India.

Future of eCommerce Logistics :

• Data driven logistics company that is bringing in same-day delivery revolution in Indonesia

• Revolutionizing delivery as an experience

• Empowering D2C Sellers with logistics as the core technology

About the Role :

• Create and maintain optimal data pipeline architecture,
• Assemble large, complex data sets that meet functional / non-functional business requirements.
• 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 SQL and AWS ‘big data’ technologies.
• Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics.
• Work with stakeholders including the 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 AWS 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.
• Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases
• Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
• Working knowledge of message queuing, stream processing, and highly scalable ‘big data’ data stores.
• Prior experience on working on Big Query, Redshift or other data warehouses

About the Company:

This opportunity is for an AI Drone Technology startup funded by the Indian Army. It is working to develop cutting-edge products to help the Indian Army gain an edge in New Age Enemy Warfare.

They are working on using drones to neutralize terrorists hidden in deep forests. Get a chance to contribute to secure our borders against the enemy.

Responsibilities:

• Extensive knowledge in machine learning and deep learning techniques
• Solid background in image processing/computer vision
• Experience in building datasets for computer vision tasks
• Experience working with and creating data structures/architectures
• Proficiency in at least one major machine learning framework such as Tensorflow, Pytorch
• Experience visualizing data to stakeholders
• Ability to analyze and debug complex algorithms
• Highly skilled in Python scripting language
• Creativity and curiosity for solving highly complex problems
• Excellent communication and collaboration skills

Educational Qualification:

MS in Engineering, Applied Mathematics, Data Science, Computer Science or equivalent field, with 3 years industry experience, a PhD degree or equivalent industry experience.

Role and Responsibilities

• Execute data mining projects, training and deploying models over a typical duration of 2 -12 months.
• The ideal candidate should be able to innovate, analyze the customer requirement, develop a solution in the time box of the project plan, execute and deploy the solution.
• Integrate the data mining projects embedded data mining applications in the FogHorn platform (on Docker or Android).

Core Qualifications
Candidates must meet ALL of the following qualifications:

• Have analyzed, trained and deployed at least three data mining models in the past. If the candidate did not directly deploy their own models, they will have worked with others who have put their models into production. The models should have been validated as robust over at least an initial time period.
• Three years of industry work experience, developing data mining models which were deployed and used.
• Programming experience in Python is core using data mining related libraries like Scikit-Learn. Other relevant Python mining libraries include NumPy, SciPy and Pandas.
• Data mining algorithm experience in at least 3 algorithms across: prediction (statistical regression, neural nets, deep learning, decision trees, SVM, ensembles), clustering (k-means, DBSCAN or other) or Bayesian networks

Bonus Qualifications
Any of the following extra qualifications will make a candidate more competitive:

• Soft Skills
  • Sets expectations, develops project plans and meets expectations.
  • Experience adapting technical dialogue to the right level for the audience (i.e. executives) or specific jargon for a given vertical market and job function.
• Technical skills
  • Commonly, candidates have a MS or Ph.D. in Computer Science, Math, Statistics or an engineering technical discipline. BS candidates with experience are considered.
  • Have managed past models in production over their full life cycle until model replacement is needed. Have developed automated model refreshing on newer data. Have developed frameworks for model automation as a prototype for product.
  • Training or experience in Deep Learning, such as TensorFlow, Keras, convolutional neural networks (CNN) or Long Short Term Memory (LSTM) neural network architectures. If you don’t have deep learning experience, we will train you on the job.
  • Shrinking deep learning models, optimizing to speed up execution time of scoring or inference.
  • OpenCV or other image processing tools or libraries
  • Cloud computing: Google Cloud, Amazon AWS or Microsoft Azure. We have integration with Google Cloud and are working on other integrations.
  • Decision trees like XGBoost or Random Forests is helpful.
  • Complex Event Processing (CEP) or other streaming data as a data source for data mining analysis
  • Time series algorithms from ARIMA to LSTM to Digital Signal Processing (DSP).
  • Bayesian Networks (BN), a.k.a. Bayesian Belief Networks (BBN) or Graphical Belief Networks (GBN)
  • Experience with PMML is of interest (see www.DMG.org).
• Vertical experience in Industrial Internet of Things (IoT) applications:
  • Energy: Oil and Gas, Wind Turbines
  • Manufacturing: Motors, chemical processes, tools, automotive
  • Smart Cities: Elevators, cameras on population or cars, power grid
  • Transportation: Cars, truck fleets, trains

About FogHorn Systems
FogHorn is a leading developer of “edge intelligence” software for industrial and commercial IoT application solutions. FogHorn’s Lightning software platform brings the power of advanced analytics and machine learning to the on-premise edge environment enabling a new class of applications for advanced monitoring and diagnostics, machine performance optimization, proactive maintenance and operational intelligence use cases. FogHorn’s technology is ideally suited for OEMs, systems integrators and end customers in manufacturing, power and water, oil and gas, renewable energy, mining, transportation, healthcare, retail, as well as Smart Grid, Smart City, Smart Building and connected vehicle applications.

Press:  https://www.foghorn.io/press-room/">https://www.foghorn.io/press-room/

Awards: https://www.foghorn.io/awards-and-recognition/">https://www.foghorn.io/awards-and-recognition/

• 2019 Edge Computing Company of the Year – Compass Intelligence
• 2019 Internet of Things 50: 10 Coolest Industrial IoT Companies – CRN
• 2018 IoT Planforms Leadership Award & Edge Computing Excellence – IoT Evolution World Magazine
• 2018 10 Hot IoT Startups to Watch – Network World. (Gartner estimated 20 billion connected things in use worldwide by 2020)
• 2018 Winner in Artificial Intelligence and Machine Learning – Globe Awards
• 2018 Ten Edge Computing Vendors to Watch – ZDNet & 451 Research
• 2018 The 10 Most Innovative AI Solution Providers – Insights Success
• 2018 The AI 100 – CB Insights
• 2017 Cool Vendor in IoT Edge Computing – Gartner
• 2017 20 Most Promising AI Service Providers – CIO Review

Our Series A round was for $15 million.  Our Series B round was for $30 million October 2017.  Investors include: Saudi Aramco Energy Ventures, Intel Capital, GE, Dell, Bosch, Honeywell and The Hive.

About the Data Science Solutions team
In 2018, our Data Science Solutions team grew from 4 to 9.  We are growing again from 11. We work on revenue generating projects for clients, such as predictive maintenance, time to failure, manufacturing defects.  About half of our projects have been related to vision recognition or deep learning. We are not only working on consulting projects but developing vertical solution applications that run on our Lightning platform, with embedded data mining.

Our data scientists like our team because:

• We care about “best practices”
• Have a direct impact on the company’s revenue
• Give or receive mentoring as part of the collaborative process
• Questions and challenging the status quo with data is safe
• Intellectual curiosity balanced with humility
• Present papers or projects in our “Thought Leadership” meeting series, to support continuous learning