11+ Intelligence Jobs in Pune | Intelligence Job openings in Pune

Job Responsibilities

• Design, build & test ETL processes using Python & SQL for the corporate data warehouse
• Inform, influence, support, and execute our product decisions
• Maintain advertising data integrity by working closely with R&D to organize and store data in a format that provides accurate data and allows the business to quickly identify issues.
• Evaluate and prototype new technologies in the area of data processing
• Think quickly, communicate clearly and work collaboratively with product, data, engineering, QA and operations teams
• High energy level, strong team player and good work ethic
• Data analysis, understanding of business requirements and translation into logical pipelines & processes
• Identification, analysis & resolution of production & development bugs
• Support the release process including completing & reviewing documentation
• Configure data mappings & transformations to orchestrate data integration & validation
• Provide subject matter expertise
• Document solutions, tools & processes
• Create & support test plans with hands-on testing
• Peer reviews of work developed by other data engineers within the team
• Establish good working relationships & communication channels with relevant departments

Skills and Qualifications we look for

• University degree 2.1 or higher (or equivalent) in a relevant subject. Master’s degree in any data subject will be a strong advantage.
• 4 - 6 years experience with data engineering.
• Strong coding ability and software development experience in Python.
• Strong hands-on experience with SQL and Data Processing.
• Google cloud platform (Cloud composer, Dataflow, Cloud function, Bigquery, Cloud storage, dataproc)
• Good working experience in any one of the ETL tools (Airflow would be preferable).
• Should possess strong analytical and problem solving skills.
• Good to have skills - Apache pyspark, CircleCI, Terraform
• Motivated, self-directed, able to work with ambiguity and interested in emerging technologies, agile and collaborative processes.
• Understanding & experience of agile / scrum delivery methodology

Graas uses predictive AI to turbo-charge growth for eCommerce businesses. We are “Growth-as-a-Service”. Graas is a technology solution provider using predictive AI to turbo-charge growth for eCommerce businesses. Graas integrates traditional data silos and applies a machine-learning AI engine, acting as an in-house data scientist to predict trends and give real-time insights and actionable recommendations for brands. The platform can also turn insights into action by seamlessly executing these recommendations across marketplace store fronts, brand.coms, social and conversational commerce, performance marketing, inventory management, warehousing, and last mile logistics - all of which impacts a brand’s bottom line, driving profitable growth.

Roles & Responsibilities:

Work on implementation of real-time and batch data pipelines for disparate data sources.

• Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS technologies.
• Build and maintain an analytics layer that utilizes the underlying data to generate dashboards and provide actionable insights.
• Identify improvement areas in the current data system and implement optimizations.
• Work on specific areas of data governance including metadata management and data quality management.
• Participate in discussions with Product Management and Business stakeholders to understand functional requirements and interact with other cross-functional teams as needed to develop, test, and release features.
• Develop Proof-of-Concepts to validate new technology solutions or advancements.
• Work in an Agile Scrum team and help with planning, scoping and creation of technical solutions for the new product capabilities, through to continuous delivery to production.
• Work on building intelligent systems using various AI/ML algorithms. 

Desired Experience/Skill:

• Must have worked on Analytics Applications involving Data Lakes, Data Warehouses and Reporting Implementations.
• Experience with private and public cloud architectures with pros/cons.
• Ability to write robust code in Python and SQL for data processing. Experience in libraries such as Pandas is a must; knowledge of one of the frameworks such as Django or Flask is a plus.
• Experience in implementing data processing pipelines using AWS services: Kinesis, Lambda, Redshift/Snowflake, RDS.
• Knowledge of Kafka, Redis is preferred
• Experience on design and implementation of real-time and batch pipelines. Knowledge of Airflow is preferred.
• Familiarity with machine learning frameworks (like Keras or PyTorch) and libraries (like scikit-learn)

We are looking for a Data Analyst that oversees organisational data analytics. This will require you to design and help implement the data analytics platform that will keep the organisation running. The team will be the go-to for all data needs for the app and we are looking for a self-starter who is hands on and yet able to abstract problems and anticipate data requirements.
This person should be very strong technical data analyst who can design and implement data systems on his own. Along with him, he also needs to be proficient in business reporting and should have keen interest in provided data needed for business.

Tools familiarity:  SQL, Python, Mix panel, Metabase, Google Analytics,  Clever Tap, App Analytics

Responsibilities

• Processes and frameworks for metrics, analytics, experimentation and user insights, lead the data analytics team
• Metrics alignment across teams to make them actionable and promote accountability
• Data based frameworks for assessing and strengthening Product Market Fit
• Identify viable growth strategies through data and experimentation
• Experimentation for product optimisation and understanding user behaviour
• Structured approach towards deriving user insights, answer questions using data
• This person needs to closely work with Technical and Business teams to get this implemented.

Skills

• 4 to 6 years at a relevant role in data analytics in a Product Oriented company
• Highly organised, technically sound & good at communication
• Ability to handle & build for cross functional data requirements / interactions with teams
• Great with Python, SQL
• Can build, mentor a team
• Knowledge of key business metrics like cohort, engagement cohort, LTV, ROAS, ROE

Eligibility

BTech or MTech in Computer Science/Engineering from a Tier1, Tier2 colleges

Good knowledge on Data Analytics, Data Visualization tools. A formal certification would be added advantage.

We are more interested in what you CAN DO than your location, education, or experience levels.

Send us your code samples / GitHub profile / published articles if applicable.

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.

https://elop.no/

https://www.simplifai.ai/en/

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

• 6+ years of recent hands-on Java development
• Developing data pipelines in AWS or Google Cloud
• Java, Python, JavaScript programming languages
• Great understanding of designing for performance, scalability, and reliability of data intensive application
• Hadoop MapReduce, Spark, Pig. Understanding of database fundamentals and advanced SQL knowledge.
• In-depth understanding of object oriented programming concepts and design patterns
• Ability to communicate clearly to technical and non-technical audiences, verbally and in writing
• Understanding of full software development life cycle, agile development and continuous integration
• Experience in Agile methodologies including Scrum and Kanban

• 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 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 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 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 identify 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.
• Working knowledge of message queuing, stream processing, and highly scalable ‘big data’ data stores.
• Strong project management and organizational skills.
• Experience supporting and working with cross-functional teams in a dynamic environment.
• We are looking for a candidate with 5+ 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.

•  3+ years of experience in Machine Learning
• Bachelors/Masters in Computer Engineering/Science.
• Bachelors/Masters in Engineering/Mathematics/Statistics with sound knowledge of programming and computer concepts.
• 10 and 12th acedemics 70 % & above.

Skills :
 - Strong Python/ programming skills
 - Good conceptual understanding of Machine Learning/Deep Learning/Natural Language            Processing
 - Strong verbal and written communication skills.
 - Should be able to manage team, meet project deadlines and interface with clients.
 - Should be able to work across different domains and quickly ramp up the business                   processes & flows & translate business problems into the data solutions

• Expertise in designing and implementing enterprise scale database (OLTP) and Data warehouse solutions.
• Hands on experience in implementing Azure SQL Database, Azure SQL Date warehouse (Azure Synapse Analytics) and big data processing using Azure Databricks and Azure HD Insight.
• Expert in writing T-SQL programming for complex stored procedures, functions, views and query optimization.
• Should be aware of Database development for both on-premise and SAAS Applications using SQL Server and PostgreSQL.
• Experience in ETL and ELT implementations using Azure Data Factory V2 and SSIS.
• Experience and expertise in building machine learning models using Logistic and linear regression, Decision tree  and Random forest Algorithms.
• PolyBase queries for exporting and importing data into Azure Data Lake.
• Building data models both tabular and multidimensional using SQL Server data tools.
• Writing data preparation, cleaning and processing steps using Python, SCALA, and R.
• Programming experience using python libraries NumPy, Pandas and Matplotlib.
• Implementing NOSQL databases and writing queries using cypher.
• Designing end user visualizations using Power BI, QlikView and Tableau.
• Experience working with all versions of SQL Server 2005/2008/2008R2/2012/2014/2016/2017/2019
• Experience using the expression languages MDX and DAX.
• Experience in migrating on-premise SQL server database to Microsoft Azure.
• Hands on experience in using Azure blob storage, Azure Data Lake Storage Gen1 and Azure Data Lake Storage Gen2.
• Performance tuning complex SQL queries, hands on experience using SQL Extended events.
• Data modeling using Power BI for Adhoc reporting.
• Raw data load automation using T-SQL and SSIS
• Expert in migrating existing on-premise database to SQL Azure.
• Experience in using U-SQL for Azure Data Lake Analytics.
• Hands on experience in generating SSRS reports using MDX.
• Experience in designing predictive models using Python and SQL Server.
• Developing machine learning models using Azure Databricks and SQL Server