- Developing telemetry software to connect Junos devices to the cloud
- Fast prototyping and laying the SW foundation for product solutions
- Moving prototype solutions to a production cloud multitenant SaaS solution
- Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources
- Build analytics tools that utilize the data pipeline to provide significant insights into customer acquisition, operational efficiency and other key business performance metrics.
- Work with partners including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs.
- 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 specialists to strive for greater functionality in our data systems.
Qualification and Desired Experiences
- Master in Computer Science, Electrical Engineering, Statistics, Applied Math or equivalent fields with strong mathematical background
- 5+ years experiences building data pipelines for data science-driven solutions
- Strong hands-on coding skills (preferably in Python) processing large-scale data set and developing machine learning model
- Familiar with one or more machine learning or statistical modeling tools such as Numpy, ScikitLearn, MLlib, Tensorflow
- Good team worker with excellent interpersonal skills written, verbal and presentation
- Create and maintain optimal data pipeline architecture,
- Assemble large, sophisticated 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.
- Experience with AWS, S3, Flink, Spark, Kafka, Elastic Search
- Previous work in a start-up environment
- 3+ years experiences building data pipelines for data science-driven solutions
- Master in Computer Science, Electrical Engineering, Statistics, Applied Math or equivalent fields with strong mathematical background
- We are looking for a candidate with 9+ years of experience in a Data Engineer role, who has attained a Graduate degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field. They should also have experience using the following software/tools:
- Experience with big data tools: Hadoop, Spark, Kafka, etc.
- Experience with relational SQL and NoSQL databases, including Postgres and Cassandra.
- Experience with data pipeline and workflow management tools: Azkaban, Luigi, Airflow, etc.
- Experience with AWS cloud services: EC2, EMR, RDS, Redshift
- Experience with stream-processing systems: Storm, Spark-Streaming, etc.
- Experience with object-oriented/object function scripting languages: Python, Java, C++, Scala, etc.
- Strong hands-on coding skills (preferably in Python) processing large-scale data set and developing machine learning model
- Familiar with one or more machine learning or statistical modeling tools such as Numpy, ScikitLearn, MLlib, Tensorflow
- Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.
- Experience building and optimizing ‘big data’ data pipelines, architectures and data sets.
- Experience performing root cause analysis on internal and external data and processes to answer specific business questions and find opportunities for improvement.
- Strong analytic skills related to working with unstructured datasets.
- Build processes supporting data transformation, data structures, metadata, dependency and workload management.
- A successful history of manipulating, processing and extracting value from large disconnected datasets.
- Proven understanding of message queuing, stream processing, and highly scalable ‘big data’ data stores.
- Strong project management and interpersonal skills.
- Experience supporting and working with multi-functional teams in a multidimensional environment.
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Management, Accounts, Regulatory Reporting, Operations, Risk, Compliance, HR on all data collection and reporting use cases.
Collaborate with Business and Technology teams to understand enterprise data, create an innovative narrative to explain, engage and enlighten regular staff members as well as executive leadership with data-driven storytelling
Solve data consumption and visualization through data as a service distribution model
Articulate findings clearly and concisely for different target use cases, including through presentations, design solutions, visualizations
Perform Adhoc / automated report generation tasks using Power BI, Oracle BI, Informatica
Perform data access/transfer and ETL automation tasks using Python, SQL, OLAP / OLTP, RESTful APIs, and IT tools (CFT, MQ-Series, Control-M, etc.)
Provide support and maintain the availability of BI applications irrespective of the hosting location
Resolve issues escalated from Business and Functional areas on data quality, accuracy, and availability, provide incident-related communications promptly
Work with strict deadlines on high priority regulatory reports
Serve as a liaison between business and technology to ensure that data related business requirements for protecting sensitive data are clearly defined, communicated, and well understood, and considered as part of operational
prioritization and planning
To work for APAC Chief Data Office and coordinate with a fully decentralized team across different locations in APAC and global HQ (Paris).
General Skills:
Excellent knowledge of RDBMS and hands-on experience with complex SQL is a must, some experience in NoSQL and Big Data Technologies like Hive and Spark would be a plus
Experience with industrialized reporting on BI tools like PowerBI, Informatica
Knowledge of data related industry best practices in the highly regulated CIB industry, experience with regulatory report generation for financial institutions
Knowledge of industry-leading data access, data security, Master Data, and Reference Data Management, and establishing data lineage
5+ years experience on Data Visualization / Business Intelligence / ETL developer roles
Ability to multi-task and manage various projects simultaneously
Attention to detail
Ability to present to Senior Management, ExCo; excellent written and verbal communication skills
● Research and develop advanced statistical and machine learning models for
analysis of large-scale, high-dimensional data.
● Dig deeper into data, understand characteristics of data, evaluate alternate
models and validate hypotheses through theoretical and empirical approaches.
● Productize has proven or working models into production-quality code.
● Collaborate with product management, marketing, and engineering teams in
Business Units to elicit & understand their requirements & challenges and
develop potential solutions
● Stay current with the latest research and technology ideas; share knowledge by
clearly articulating results and ideas to key decision-makers.
● File patents for innovative solutions that add to the company's IP portfolio
Requirements
● 4 to 6 years of strong experience in data mining, machine learning and
statistical analysis.
● BS/MS/Ph.D. in Computer Science, Statistics, Applied Math, or related areas
from Premier institutes ( only IITs / IISc / BITS / Top NITs or top US university
should apply)
● Experience in productizing models to code in a fast-paced start-up
environment.
● Fluency in analytical tools such as Matlab, R, Weka etc.
● Strong intuition for data and Keen aptitude on large scale data analysis
● Strong communication and collaboration skills.
Job Description:
The data science team is responsible for solving business problems with complex data. Data complexity could be characterized in terms of volume, dimensionality and multiple touchpoints/sources. We understand the data, ask fundamental-first-principle questions, apply our analytical and machine learning skills to solve the problem in the best way possible.
Our ideal candidate
The role would be a client facing one, hence good communication skills are a must.
The candidate should have the ability to communicate complex models and analysis in a clear and precise manner.
The candidate would be responsible for:
- Comprehending business problems properly - what to predict, how to build DV, what value addition he/she is bringing to the client, etc.
- Understanding and analyzing large, complex, multi-dimensional datasets and build features relevant for business
- Understanding the math behind algorithms and choosing one over another
- Understanding approaches like stacking, ensemble and applying them correctly to increase accuracy
Desired technical requirements
- Proficiency with Python and the ability to write production-ready codes.
- Experience in pyspark, machine learning and deep learning
- Big data experience, e.g. familiarity with Spark, Hadoop, is highly preferred
- Familiarity with SQL or other databases.
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/
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
Bigdata with cloud:
Experience : 5-10 years
Location : Hyderabad/Chennai
Notice period : 15-20 days Max
1. Expertise in building AWS Data Engineering pipelines with AWS Glue -> Athena -> Quick sight
2. Experience in developing lambda functions with AWS Lambda
3. Expertise with Spark/PySpark – Candidate should be hands on with PySpark code and should be able to do transformations with Spark
4. Should be able to code in Python and Scala.
5. Snowflake experience will be a plus
We are looking for a skilled Senior/Lead Bigdata Engineer to join our team. The role is part of the research and development team, where you with enthusiasm and knowledge are going to be our technical evangelist for the development of our inspection technology and products.
At Elop we are developing product lines for sustainable infrastructure management using our own patented technology for ultrasound scanners and combine this with other sources to see holistic overview of the concrete structure. At Elop we will provide you with world-class colleagues highly motivated to position the company as an international standard of structural health monitoring. With the right character you will be professionally challenged and developed.
This position requires travel to Norway.
Elop is sister company of Simplifai and co-located together in all geographic locations.
Roles and Responsibilities
- Define technical scope and objectives through research and participation in requirements gathering and definition of processes
- Ingest and Process data from data sources (Elop Scanner) in raw format into Big Data ecosystem
- Realtime data feed processing using Big Data ecosystem
- Design, review, implement and optimize data transformation processes in Big Data ecosystem
- Test and prototype new data integration/processing tools, techniques and methodologies
- Conversion of MATLAB code into Python/C/C++.
- Participate in overall test planning for the application integrations, functional areas and projects.
- Work with cross functional teams in an Agile/Scrum environment to ensure a quality product is delivered.
Desired Candidate Profile
- Bachelor's degree in Statistics, Computer or equivalent
- 7+ years of experience in Big Data ecosystem, especially Spark, Kafka, Hadoop, HBase.
- 7+ years of hands-on experience in Python/Scala is a must.
- Experience in architecting the big data application is needed.
- Excellent analytical and problem solving skills
- Strong understanding of data analytics and data visualization, and must be able to help development team with visualization of data.
- Experience with signal processing is plus.
- Experience in working on client server architecture is plus.
- Knowledge about database technologies like RDBMS, Graph DB, Document DB, Apache Cassandra, OpenTSDB
- Good communication skills, written and oral, in English
We can Offer
- An everyday life with exciting and challenging tasks with the development of socially beneficial solutions
- Be a part of companys research and Development team to create unique and innovative products
- Colleagues with world-class expertise, and an organization that has ambitions and is highly motivated to position the company as an international player in maintenance support and monitoring of critical infrastructure!
- Good working environment with skilled and committed colleagues an organization with short decision paths.
- Professional challenges and development
Designation: Specialist - Cloud Service Developer (ABL_SS_600)
Position description:
- The person would be primary responsible for developing solutions using AWS services. Ex: Fargate, Lambda, ECS, ALB, NLB, S3 etc.
- Apply advanced troubleshooting techniques to provide Solutions to issues pertaining to Service Availability, Performance, and Resiliency
- Monitor & Optimize the performance using AWS dashboards and logs
- Partner with Engineering leaders and peers in delivering technology solutions that meet the business requirements
- Work with the cloud team in agile approach and develop cost optimized solutions
Primary Responsibilities:
- Develop solutions using AWS services includiing Fargate, Lambda, ECS, ALB, NLB, S3 etc.
Reporting Team
- Reporting Designation: Head - Big Data Engineering and Cloud Development (ABL_SS_414)
- Reporting Department: Application Development (2487)
Required Skills:
- AWS certification would be preferred
- Good understanding in Monitoring (Cloudwatch, alarms, logs, custom metrics, Trust SNS configuration)
- Good experience with Fargate, Lambda, ECS, ALB, NLB, S3, Glue, Aurora and other AWS services.
- Preferred to have Knowledge on Storage (S3, Life cycle management, Event configuration)
- Good in data structure, programming in (pyspark / python / golang / Scala)
Understand various raw data input formats, build consumers on Kafka/ksqldb for them and ingest large amounts of raw data into Flink and Spark.
Conduct complex data analysis and report on results.
Build various aggregation streams for data and convert raw data into various logical processing streams.
Build algorithms to integrate multiple sources of data and create a unified data model from all the sources.
Build a unified data model on both SQL and NO-SQL databases to act as data sink.
Communicate the designs effectively with the fullstack engineering team for development.
Explore machine learning models that can be fitted on top of the data pipelines.
Mandatory Qualifications Skills:
Deep knowledge of Scala and Java programming languages is mandatory
Strong background in streaming data frameworks (Apache Flink, Apache Spark) is mandatory
Good understanding and hands on skills on streaming messaging platforms such as Kafka
Familiarity with R, C and Python is an asset
Analytical mind and business acumen with strong math skills (e.g. statistics, algebra)
Problem-solving aptitude
Excellent communication and presentation skills