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For a leading manufacturing company
Database Architect |
5 - 6 Years |
Good Knowledge in Relation and Non-Relational Database |
To write Complex Queries and Identify problematic queries and provide a Solution |
Good Hands on database tools |
Experience in Both SQL and NON SQL Database like SQL Server, PostgreSQL, Mango DB, Maria DB. Etc. |
Worked on Data Model Preparation & Structuring Database etc. |
Location: Chennai
Education: BE/BTech
Experience: Minimum 3+ years of experience as a Data Scientist/Data Engineer
Domain knowledge: Data cleaning, modelling, analytics, statistics, machine learning, AI
Requirements:
- To be part of Digital Manufacturing and Industrie 4.0 projects across client group of companies
- Design and develop AI//ML models to be deployed across factories
- Knowledge on Hadoop, Apache Spark, MapReduce, Scala, Python programming, SQL and NoSQL databases is required
- Should be strong in statistics, data analysis, data modelling, machine learning techniques and Neural Networks
- Prior experience in developing AI and ML models is required
- Experience with data from the Manufacturing Industry would be a plus
Roles and Responsibilities:
- Develop AI and ML models for the Manufacturing Industry with a focus on Energy, Asset Performance Optimization and Logistics
- Multitasking, good communication necessary
- Entrepreneurial attitude
Additional Information:
- Travel: Must be willing to travel on shorter duration within India and abroad
- Job Location: Chennai
- Reporting to: Team Leader, Energy Management System
at AxionConnect Infosolutions Pvt Ltd
Job Location: Hyderabad/Bangalore/ Chennai/Pune/Nagpur
Notice period: Immediate - 15 days
1. Python Developer with Snowflake
Job Description :
- 5.5+ years of Strong Python Development Experience with Snowflake.
- Strong hands of experience with SQL ability to write complex queries.
- Strong understanding of how to connect to Snowflake using Python, should be able to handle any type of files
- Development of Data Analysis, Data Processing engines using Python
- Good Experience in Data Transformation using Python.
- Experience in Snowflake data load using Python.
- Experience in creating user-defined functions in Snowflake.
- Snowsql implementation.
- Knowledge of query performance tuning will be added advantage.
- Good understanding of Datawarehouse (DWH) concepts.
- Interpret/analyze business requirements & functional specification
- Good to have DBT, FiveTran, and AWS Knowledge.
Data Engineer- Senior
Cubera is a data company revolutionizing big data analytics and Adtech through data share value principles wherein the users entrust their data to us. We refine the art of understanding, processing, extracting, and evaluating the data that is entrusted to us. We are a gateway for brands to increase their lead efficiency as the world moves towards web3.
What are you going to do?
Design & Develop high performance and scalable solutions that meet the needs of our customers.
Closely work with the Product Management, Architects and cross functional teams.
Build and deploy large-scale systems in Java/Python.
Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
Create data tools for analytics and data scientist team members that assist them in building and optimizing their algorithms.
Follow best practices that can be adopted in Bigdata stack.
Use your engineering experience and technical skills to drive the features and mentor the engineers.
What are we looking for ( Competencies) :
Bachelor’s degree in computer science, computer engineering, or related technical discipline.
Overall 5 to 8 years of programming experience in Java, Python including object-oriented design.
Data handling frameworks: Should have a working knowledge of one or more data handling frameworks like- Hive, Spark, Storm, Flink, Beam, Airflow, Nifi etc.
Data Infrastructure: Should have experience in building, deploying and maintaining applications on popular cloud infrastructure like AWS, GCP etc.
Data Store: Must have expertise in one of general-purpose No-SQL data stores like Elasticsearch, MongoDB, Redis, RedShift, etc.
Strong sense of ownership, focus on quality, responsiveness, efficiency, and innovation.
Ability to work with distributed teams in a collaborative and productive manner.
Benefits:
Competitive Salary Packages and benefits.
Collaborative, lively and an upbeat work environment with young professionals.
Job Category: Development
Job Type: Full Time
Job Location: Bangalore
Responsibilities:
• Designing Hive/HCatalog data model includes creating table definitions, file formats, compression techniques for Structured & Semi-structured data processing
• Implementing Spark processing based ETL frameworks
• Implementing Big data pipeline for Data Ingestion, Storage, Processing & Consumption
• Modifying the Informatica-Teradata & Unix based data pipeline
• Enhancing the Talend-Hive/Spark & Unix based data pipelines
• Develop and Deploy Scala/Python based Spark Jobs for ETL processing
• Strong SQL & DWH concepts.
Preferred Background:
• Function as integrator between business needs and technology solutions, helping to create technology solutions to meet clients’ business needs
• Lead project efforts in defining scope, planning, executing, and reporting to stakeholders on strategic initiatives
• Understanding of EDW system of business and creating High level design document and low level implementation document
• Understanding of Big Data Lake system of business and creating High level design document and low level implementation document
• Designing Big data pipeline for Data Ingestion, Storage, Processing & Consumption
Responsibilities:
- Be the analytical expert in Kaleidofin, managing ambiguous problems by using data to execute sophisticated quantitative modeling and deliver actionable insights.
- Develop comprehensive skills including project management, business judgment, analytical problem solving and technical depth.
- Become an expert on data and trends, both internal and external to Kaleidofin.
- Communicate key state of the business metrics and develop dashboards to enable teams to understand business metrics independently.
- Collaborate with stakeholders across teams to drive data analysis for key business questions, communicate insights and drive the planning process with company executives.
- Automate scheduling and distribution of reports and support auditing and value realization.
- Partner with enterprise architects to define and ensure proposed.
- Business Intelligence solutions adhere to an enterprise reference architecture.
- Design robust data-centric solutions and architecture that incorporates technology and strong BI solutions to scale up and eliminate repetitive tasks.
- Experience leading development efforts through all phases of SDLC.
- 2+ years "hands-on" experience designing Analytics and Business Intelligence solutions.
- Experience with Quicksight, PowerBI, Tableau and Qlik is a plus.
- Hands on experience in SQL, data management, and scripting (preferably Python).
- Strong data visualisation design skills, data modeling and inference skills.
- Hands-on and experience in managing small teams.
- Financial services experience preferred, but not mandatory.
- Strong knowledge of architectural principles, tools, frameworks, and best practices.
- Excellent communication and presentation skills to communicate and collaborate with all levels of the organisation.
- Preferred candidates with less than 30 days notice period.
• S/he possesses a wide exposure to complete lifecycle of data starting from creation to consumption
• S/he has in the past built repeatable tools / data-models to solve specific business problems
• S/he should have hand-on experience of having worked on projects (either as a consultant or with in a company) that needed them to
o Provide consultation to senior client personnel o Implement and enhance data warehouses or data lakes.
o Worked with business teams or was a part of the team that implemented process re-engineering driven by data analytics/insights
• Should have deep appreciation of how data can be used in decision-making
• Should have perspective on newer ways of solving business problems. E.g. external data, innovative techniques, newer technology
• S/he must have a solution-creation mindset.
Ability to design and enhance scalable data platforms to address the business need
• Working experience on data engineering tool for one or more cloud platforms -Snowflake, AWS/Azure/GCP
• Engage with technology teams from Tredence and Clients to create last mile connectivity of the solutions
o Should have experience of working with technology teams
• Demonstrated ability in thought leadership – Articles/White Papers/Interviews
Mandatory Skills Program Management, Data Warehouse, Data Lake, Analytics, Cloud Platform
Position: Big Data Engineer
What You'll Do
Punchh is seeking to hire Big Data Engineer at either a senior or tech lead level. Reporting to the Director of Big Data, he/she will play a critical role in leading Punchh’s big data innovations. By leveraging prior industrial experience in big data, he/she will help create cutting-edge data and analytics products for Punchh’s business partners.
This role requires close collaborations with data, engineering, and product organizations. His/her job functions include
- Work with large data sets and implement sophisticated data pipelines with both structured and structured data.
- Collaborate with stakeholders to design scalable solutions.
- Manage and optimize our internal data pipeline that supports marketing, customer success and data science to name a few.
- A technical leader of Punchh’s big data platform that supports AI and BI products.
- Work with infra and operations team to monitor and optimize existing infrastructure
- Occasional business travels are required.
What You'll Need
- 5+ years of experience as a Big Data engineering professional, developing scalable big data solutions.
- Advanced degree in computer science, engineering or other related fields.
- Demonstrated strength in data modeling, data warehousing and SQL.
- Extensive knowledge with cloud technologies, e.g. AWS and Azure.
- Excellent software engineering background. High familiarity with software development life cycle. Familiarity with GitHub/Airflow.
- Advanced knowledge of big data technologies, such as programming language (Python, Java), relational (Postgres, mysql), NoSQL (Mongodb), Hadoop (EMR) and streaming (Kafka, Spark).
- Strong problem solving skills with demonstrated rigor in building and maintaining a complex data pipeline.
- Exceptional communication skills and ability to articulate a complex concept with thoughtful, actionable recommendations.
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