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Designation – Deputy Manager - TS
Job Description
- Total of 8/9 years of development experience Data Engineering . B1/BII role
- Minimum of 4/5 years in AWS Data Integrations and should be very good on Data modelling skills.
- 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.
- Should have experience in delivering at least 4 Data Warehouse or Data Lake Solutions on AWS.
- Should be very strong experience on Glue, Lambda, Data Pipeline, Step functions, RDS, CloudFormation etc.
- Strong Python skill .
- Should be an expert in Cloud design principles, Performance tuning and cost modelling. AWS certifications will have an added advantage
- Should be a team player with Excellent communication and should be able to manage his work independently with minimal or no supervision.
- Life Science & Healthcare domain background will be a plus
Qualifications
BE/Btect/ME/MTech
Proficiency in Linux.
Must have SQL knowledge and experience working with relational databases,
query authoring (SQL) as well as familiarity with databases including Mysql,
Mongo, Cassandra, and Athena.
Must have experience with Python/Scala.
Must have experience with Big Data technologies like Apache Spark.
Must have experience with Apache Airflow.
Experience with data pipeline and ETL tools like AWS Glue.
Experience working with AWS cloud services: EC2, S3, RDS, Redshift.
Design, implement, and improve the analytics platform
Implement and simplify self-service data query and analysis capabilities of the BI platform
Develop and improve the current BI architecture, emphasizing data security, data quality
and timeliness, scalability, and extensibility
Deploy and use various big data technologies and run pilots to design low latency
data architectures at scale
Collaborate with business analysts, data scientists, product managers, software development engineers,
and other BI teams to develop, implement, and validate KPIs, statistical analyses, data profiling, prediction,
forecasting, clustering, and machine learning algorithms
Educational
At Ganit we are building an elite team, ergo we are seeking candidates who possess the
following backgrounds:
7+ years relevant experience
Expert level skills writing and optimizing complex SQL
Knowledge of data warehousing concepts
Experience in data mining, profiling, and analysis
Experience with complex data modelling, ETL design, and using large databases
in a business environment
Proficiency with Linux command line and systems administration
Experience with languages like Python/Java/Scala
Experience with Big Data technologies such as Hive/Spark
Proven ability to develop unconventional solutions, sees opportunities to
innovate and leads the way
Good experience of working in cloud platforms like AWS, GCP & Azure. Having worked on
projects involving creation of data lake or data warehouse
Excellent verbal and written communication.
Proven interpersonal skills and ability to convey key insights from complex analyses in
summarized business terms. Ability to effectively communicate with multiple teams
Good to have
AWS/GCP/Azure Data Engineer Certification
JOB DESCRIPTION
- 2 to 6 years of experience in imparting technical training/ mentoring
- Must have very strong concepts of Data Analytics
- Must have hands-on and training experience on Python, Advanced Python, R programming, SAS and machine learning
- Must have good knowledge of SQL and Advanced SQL
- Should have basic knowledge of Statistics
- Should be good in Operating systems GNU/Linux, Network fundamentals,
- Must have knowledge on MS office (Excel/ Word/ PowerPoint)
- Self-Motivated and passionate about technology
- Excellent analytical and logical skills and team player
- Must have exceptional Communication Skills/ Presentation Skills
- Good Aptitude skills is preferred
- Exceptional communication skills
Responsibilities:
- Ability to quickly learn any new technology and impart the same to other employees
- Ability to resolve all technical queries of students
- Conduct training sessions and drive the placement driven quality in the training
- Must be able to work independently without the supervision of a senior person
- Participate in reviews/ meetings
Qualification:
- UG: Any Graduate in IT/Computer Science, B.Tech/B.E. – IT/ Computers
- PG: MCA/MS/MSC – Computer Science
- Any Graduate/ Post graduate, provided they are certified in similar courses
ABOUT EDUBRIDGE
EduBridge is an Equal Opportunity employer and we believe in building a meritorious culture where everyone is recognized for their skills and contribution.
Launched in 2009 EduBridge Learning is a workforce development and skilling organization with 50+ training academies in 18 States pan India. The organization has been providing skilled manpower to corporates for over 10 years and is a leader in its space. We have trained over a lakh semi urban & economically underprivileged youth on relevant life skills and industry-specific skills and provided placements in over 500 companies. Our latest product E-ON is committed to complementing our training delivery with an Online training platform, enabling the students to learn anywhere and anytime.
To know more about EduBridge please visit: http://www.edubridgeindia.com/">http://www.edubridgeindia.com/
You can also visit us on https://www.facebook.com/Edubridgelearning/">Facebook , https://www.linkedin.com/company/edubridgelearning/">LinkedIn for our latest initiatives and products
- Sr. Data Engineer:
Core Skills – Data Engineering, Big Data, Pyspark, Spark SQL and Python
Candidate with prior Palantir Cloud Foundry OR Clinical Trial Data Model background is preferred
Major accountabilities:
- Responsible for Data Engineering, Foundry Data Pipeline Creation, Foundry Analysis & Reporting, Slate Application development, re-usable code development & management and Integrating Internal or External System with Foundry for data ingestion with high quality.
- Have good understanding on Foundry Platform landscape and it’s capabilities
- Performs data analysis required to troubleshoot data related issues and assist in the resolution of data issues.
- Defines company data assets (data models), Pyspark, spark SQL, jobs to populate data models.
- Designs data integrations and data quality framework.
- Design & Implement integration with Internal, External Systems, F1 AWS platform using Foundry Data Connector or Magritte Agent
- Collaboration with data scientists, data analyst and technology teams to document and leverage their understanding of the Foundry integration with different data sources - Actively participate in agile work practices
- Coordinating with Quality Engineer to ensure the all quality controls, naming convention & best practices have been followed
Desired Candidate Profile :
- Strong data engineering background
- Experience with Clinical Data Model is preferred
- Experience in
- SQL Server ,Postgres, Cassandra, Hadoop, and Spark for distributed data storage and parallel computing
- Java and Groovy for our back-end applications and data integration tools
- Python for data processing and analysis
- Cloud infrastructure based on AWS EC2 and S3
- 7+ years IT experience, 2+ years’ experience in Palantir Foundry Platform, 4+ years’ experience in Big Data platform
- 5+ years of Python and Pyspark development experience
- Strong troubleshooting and problem solving skills
- BTech or master's degree in computer science or a related technical field
- Experience designing, building, and maintaining big data pipelines systems
- Hands-on experience on Palantir Foundry Platform and Foundry custom Apps development
- Able to design and implement data integration between Palantir Foundry and external Apps based on Foundry data connector framework
- Hands-on in programming languages primarily Python, R, Java, Unix shell scripts
- Hand-on experience in AWS / Azure cloud platform and stack
- Strong in API based architecture and concept, able to do quick PoC using API integration and development
- Knowledge of machine learning and AI
- Skill and comfort working in a rapidly changing environment with dynamic objectives and iteration with users.
Demonstrated ability to continuously learn, work independently, and make decisions with minimal supervision
This position is not for freshers. We are looking for candidates with AI/ML/CV experience of at least 4 year in the industry.
• Total of 4+ years of experience in development, architecting/designing and implementing Software solutions for enterprises.
• Must have strong programming experience in either Python or Java/J2EE.
• Minimum of 4+ year’s experience working with various Cloud platforms preferably Google Cloud Platform.
• Experience in Architecting and Designing solutions leveraging Google Cloud products such as Cloud BigQuery, Cloud DataFlow, Cloud Pub/Sub, Cloud BigTable and Tensorflow will be highly preferred.
• Presentation skills with a high degree of comfort speaking with management and developers
• The ability to work in a fast-paced, work environment
• Excellent communication, listening, and influencing skills
RESPONSIBILITIES:
• Lead teams to implement and deliver software solutions for Enterprises by understanding their requirements.
• Communicate efficiently and document the Architectural/Design decisions to customer stakeholders/subject matter experts.
• Opportunity to learn new products quickly and rapidly comprehend new technical areas – technical/functional and apply detailed and critical thinking to customer solutions.
• Implementing and optimizing cloud solutions for customers.
• Migration of Workloads from on-prem/other public clouds to Google Cloud Platform.
• Provide solutions to team members for complex scenarios.
• Promote good design and programming practices with various teams and subject matter experts.
• Ability to work on any product on the Google cloud platform.
• Must be hands-on and be able to write code as required.
• Ability to lead junior engineers and conduct code reviews
QUALIFICATION:
• Minimum B.Tech/B.E Engineering graduate
along with metrics to track their progress
Managing available resources such as hardware, data, and personnel so that deadlines
are met
Analysing the ML algorithms that could be used to solve a given problem and ranking
them by their success probability
Exploring and visualizing data to gain an understanding of it, then identifying
differences in data distribution that could affect performance when deploying the model
in the real world
Verifying data quality, and/or ensuring it via data cleaning
Supervising the data acquisition process if more data is needed
Defining validation strategies
Defining the pre-processing or feature engineering to be done on a given dataset
Defining data augmentation pipelines
Training models and tuning their hyper parameters
Analysing the errors of the model and designing strategies to overcome them
Deploying models to production