Data Insights & Analyst

Job Description:

As an Azure Data Engineer, your role will involve designing, developing, and maintaining data solutions on the Azure platform. You will be responsible for building and optimizing data pipelines, ensuring data quality and reliability, and implementing data processing and transformation logic. Your expertise in Azure Databricks, Python, SQL, Azure Data Factory (ADF), PySpark, and Scala will be essential for performing the following key responsibilities:

Designing and developing data pipelines: You will design and implement scalable and efficient data pipelines using Azure Databricks, PySpark, and Scala. This includes data ingestion, data transformation, and data loading processes.

Data modeling and database design: You will design and implement data models to support efficient data storage, retrieval, and analysis. This may involve working with relational databases, data lakes, or other storage solutions on the Azure platform.

Data integration and orchestration: You will leverage Azure Data Factory (ADF) to orchestrate data integration workflows and manage data movement across various data sources and targets. This includes scheduling and monitoring data pipelines.

Data quality and governance: You will implement data quality checks, validation rules, and data governance processes to ensure data accuracy, consistency, and compliance with relevant regulations and standards.

Performance optimization: You will optimize data pipelines and queries to improve overall system performance and reduce processing time. This may involve tuning SQL queries, optimizing data transformation logic, and leveraging caching techniques.

Monitoring and troubleshooting: You will monitor data pipelines, identify performance bottlenecks, and troubleshoot issues related to data ingestion, processing, and transformation. You will work closely with cross-functional teams to resolve data-related problems.

Documentation and collaboration: You will document data pipelines, data flows, and data transformation processes. You will collaborate with data scientists, analysts, and other stakeholders to understand their data requirements and provide data engineering support.

Skills and Qualifications:

Strong experience with Azure Databricks, Python, SQL, ADF, PySpark, and Scala.

Proficiency in designing and developing data pipelines and ETL processes.

Solid understanding of data modeling concepts and database design principles.

Familiarity with data integration and orchestration using Azure Data Factory.

Knowledge of data quality management and data governance practices.

Experience with performance tuning and optimization of data pipelines.

Strong problem-solving and troubleshooting skills related to data engineering.

Excellent collaboration and communication skills to work effectively in cross-functional teams.

Understanding of cloud computing principles and experience with Azure services.

LogiNext is looking for a technically savvy and passionate Principle Engineer - Data Science to analyze large amounts of raw information to find patterns that will help improve our company. We will rely on you to build data products to extract valuable business insights.

In this role, you should be highly analytical with a knack for analysis, math and statistics. Critical thinking and problem-solving skills are essential for interpreting data. We also want to see a passion for machine-learning and research.

Your goal will be to help our company analyze trends to make better decisions. Without knowledge of how the software works, data scientists might have difficulty in work. Apart from experience in developing R and Python, they must know modern approaches to software development and their impact. DevOps continuous integration and deployment, experience in cloud computing are everyday skills to manage and process data.

Responsibilities :

Adapting and enhancing machine learning techniques based on physical intuition about the domain Design sampling methodology, prepare data, including data cleaning, univariate analysis, missing value imputation, , identify appropriate analytic and statistical methodology, develop predictive models and document process and results Lead projects both as a principal investigator and project manager, responsible for meeting project requirements on schedule and on budget Coordinate and lead efforts to innovate by deriving insights from heterogeneous sets of data generated by our suite of Aerospace products Support and mentor data scientists Maintain and work with our data pipeline that transfers and processes several terabytes of data using Spark, Scala, Python, Apache Kafka, Pig/Hive & Impala Work directly with application teams/partners (internal clients such as Xbox, Skype, Office) to understand their offerings/domain and help them become successful with data so they can run controlled experiments (a/b testing) Understand the data generated by experiments, and producing actionable, trustworthy conclusions from them Apply data analysis, data mining and data processing to present data clearly and develop experiments (ab testing) Work with development team to build tools for data logging and repeatable data tasks tol accelerate and automate data scientist duties

Requirements:

Bachelor’s or Master’s degree in Computer Science, Math, Physics, Engineering, Statistics or other technical field. PhD preferred 8 to 10 years of experience in data mining, data modeling, and reporting 5+ years of experience working with large data sets or do large scale quantitative analysis Expert SQL scripting required Development experience in one of the following: Scala, Java, Python, Perl, PHP, C++ or C# Experience working with Hadoop, Pig/Hive, Spark, MapReduce Ability to drive projects Basic understanding of statistics – hypothesis testing, p-values, confidence intervals, regression, classification, and optimization are core lingo Analysis - Should be able to perform Exploratory Data Analysis and get actionable insights from the data, with impressive visualization. Modeling - Should be familiar with ML concepts and algorithms; understanding of the internals and pros/cons of models is required. Strong algorithmic problem-solving skills Experience manipulating large data sets through statistical software (ex. R, SAS) or other methods Superior verbal, visual and written communication skills to educate and work with cross functional teams on controlled experiments Experimentation design or A/B testing experience is preferred. Experience in leading a team required.

Skills: Machine Learning,Deep Learning,Artificial Intelligence,python.

Location:Chennai


Domain knowledge: Data cleaning, modelling, analytics, statistics, machine learning, AI

Requirements:

·         To be part of Digital Manufacturing and Industrie 4.0 projects across Saint Gobain group of companies

·         Design and develop AI//ML models to be deployed across SG 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.

• 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.

• 4-10 years of experience in software development.
• At least 2 years of relevant work experience on large scale Data applications.
• Strong coding experience in Java is mandatory
• Good aptitude, strong problem solving abilities, and analytical skills, ability to take ownership as appropriate
• Should be able to do coding, debugging, performance tuning and deploying the apps to Prod.
• Should have good working experience on
• o Hadoop ecosystem (HDFS, Hive, Yarn, File formats like Avro/Parquet)
• o Kafka
• o J2EE Frameworks (Spring/Hibernate/REST)
• o Spark Streaming or any other streaming technology.
• Strong coding experience in Java is mandatory
• Ability to work on the sprint stories to completion along with Unit test case coverage.
• Experience working in Agile Methodology
• Excellent communication and coordination skills
• Knowledgeable (and preferred hands on) - UNIX environments, different continuous integration tools.
• Must be able to integrate quickly into the team and work independently towards team goals

• Take the complete responsibility of the sprint stories' execution
• Be accountable for the delivery of the tasks in the defined timelines with good quality.
• Follow the processes for project execution and delivery.
• Follow agile methodology
• Work with the team lead closely and contribute to the smooth delivery of the project.
• Understand/define the architecture and discuss the pros-cons of the same with the team
• Involve in the brainstorming sessions and suggest improvements in the architecture/design.
• Work with other team leads to get the architecture/design reviewed.
• Work with the clients and counter-parts (in US) of the project.
• Keep all the stakeholders updated about the project/task status/risks/issues if there are any.

We are an early stage start-up, building new fintech products for small businesses. Founders are IIT-IIM alumni, with prior experience across management consulting, venture capital and fintech startups. We are driven by the vision to empower small business owners with technology and dramatically improve their access to financial services. To start with, we are building a simple, yet powerful solution to address a deep pain point for these owners: cash flow management. Over time, we will also add digital banking and 1-click financing to our suite of offerings.

We have developed an MVP which is being tested in the market. We have closed our seed funding from marquee global investors and are now actively building a world class tech team. We are a young, passionate team with a strong grip on this space and are looking to on-board enthusiastic, entrepreneurial individuals to partner with us in this exciting journey. We offer a high degree of autonomy, a collaborative fast-paced work environment and most importantly, a chance to create unparalleled impact using technology.

Reach out if you want to get in on the ground floor of something which can turbocharge SME banking in India!

Technology stack at Velocity comprises a wide variety of cutting edge technologies like, NodeJS, Ruby on Rails, Reactive Programming,, Kubernetes, AWS, NodeJS, Python, ReactJS, Redux (Saga) Redis, Lambda etc. 

Key Responsibilities

• Responsible for building data and analytical engineering pipelines with standard ELT patterns, implementing data compaction pipelines, data modelling and overseeing overall data quality

• Work with the Office of the CTO as an active member of our architecture guild

• Writing pipelines to consume the data from multiple sources

• Writing a data transformation layer using DBT to transform millions of data into data warehouses.

• Implement Data warehouse entities with common re-usable data model designs with automation and data quality capabilities

• Identify downstream implications of data loads/migration (e.g., data quality, regulatory)

What To Bring

• 5+ years of software development experience, a startup experience is a plus.

• Past experience of working with Airflow and DBT is preferred

• 5+ years of experience working in any backend programming language. 

• Strong first-hand experience with data pipelines and relational databases such as Oracle, Postgres, SQL Server or MySQL

• Experience with DevOps tools (GitHub, Travis CI, and JIRA) and methodologies (Lean, Agile, Scrum, Test Driven Development)

• Experienced with the formulation of ideas; building proof-of-concept (POC) and converting them to production-ready projects

• Experience building and deploying applications on on-premise and AWS or Google Cloud cloud-based infrastructure

• Basic understanding of Kubernetes & docker is a must.

• Experience in data processing (ETL, ELT) and/or cloud-based platforms

• Working proficiency and communication skills in verbal and written English.

Role Description:

• You will be part of the data delivery team and will have the opportunity to develop a deep understanding of the domain/function.
• You will design and drive the work plan for the optimization/automation and standardization of the processes incorporating best practices to achieve efficiency gains.
• You will run data engineering pipelines, link raw client data with data model, conduct data assessment, perform data quality checks, and transform data using ETL tools.
• You will perform data transformations, modeling, and validation activities, as well as configure applications to the client context. You will also develop scripts to validate, transform, and load raw data using programming languages such as Python and / or PySpark.
• In this role, you will determine database structural requirements by analyzing client operations, applications, and programming.
• You will develop cross-site relationships to enhance idea generation, and manage stakeholders.
• Lastly, you will collaborate with the team to support ongoing business processes by delivering high-quality end products on-time and perform quality checks wherever required.

• 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 SQL and Azure ‘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 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 centres 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.

• 2+ years of experience in a Data 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 big data tools: Hadoop, Spark, Kafka, etc.
• Experience with relational SQL and NoSQL databases
• Experience with data pipeline and workflow management tools
• Experience with Azure cloud services: ADLS, ADF, ADLA, AAS
• Experience with stream-processing systems: Storm, Spark-Streaming, etc.
• Experience with object-oriented/object function scripting languages: Python, Java, C++, Scala, etc.
• 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 ELT and ETL patterns and when to use each. Understanding of data models and transforming data into the models
• Experience building and optimizing ‘big data’ data pipelines, architectures, and data sets
• Strong analytic skills related to working with unstructured datasets
• Build processes supporting data transformation, data structures, metadata, dependency, and workload management
• Working knowledge of message queuing, stream processing, and highly scalable ‘big data’ data stores
• Experience supporting and working with cross-functional teams in a dynamic environment