The unexpected shift towards the digital phase has provided us an opportunity to source, measure and analyze the cosmic data generated by businesses today. The digital shift has sparked a passion for us to see data in everything and everywhere around us. We drive digital transformation for data-intensive businesses and help them make sense of data by providing impactful insights critical for business decisions. We enable businesses to be digital savvy and data-smart.
Are you infatuated by numbers? Does data peak your curiosity level? Do you love decoding complex data? Then we believe you are ready to join our team of passionate data enterpreneurs and enthusiasts. You will be working in a fast-paced and highly motivated environment. Your colleagues and peers are equally excited about data just like you. You will work for leading corporations and interpret tonnes of data to help them overcome critical business hurdles. You will communicate via charts and graphs most of the time and always wear your thinking cap on to simplify complex data challenges.
At Phygital Insights, we believe in the learning curve. We are constantly evolving as a team and believe in learning from one another, regardless of seniority or any other hierarchy level. Our 'open door' policy allows any individual to express themselves with anyone. We want to ensure that every employee is stress-free and contributes to the overall performance and success of our organization. We inspire transparency in whatever we do and are accountable for every action we take. We are united by our passion for data, which allows us to work productively and derive results that are top-of-the-line. We bring in positivism to the environment, leaving out indifference and ego, to work in a spirited collaborative environment.
Spark (Pyspark) Developer
Experience: 6 Years
- The developer must have sound knowledge in Apache Spark and Python programming.
- Deep experience in developing data processing tasks using pySpark such as reading data from external sources, merge data, perform data enrichment and load in to target data destinations.
- Experience in deployment and operationalizing the code is added advantage – Have knowledge and skills in Devops/version control and containerization. Preferable – having deployment knowledge.
- Create Spark jobs for data transformation and aggregation
- Produce unit tests for Spark transformations and helper methods
- Write Scaladoc-style documentation with all code
- Design data processing pipelines to perform batch and Real- time/stream analytics on structured and unstructured data
- Spark query tuning and performance optimization – Good understanding of different file formats (ORC, Parquet, AVRO) to optimize queries/processing and compression techniques.
- SQL database integration (Microsoft, Oracle, Postgres, and/or MySQL)
- Experience working with (HDFS, S3, Cassandra, and/or DynamoDB)
- Deep understanding of distributed systems (e.g. CAP theorem, partitioning, replication, consistency, and consensus)
- Experience in building cloud scalable high-performance data lake solutions
- Hands on expertise in cloud services like AWS, and/or Microsoft Azure.
Azure Senior Developer
Experience: 6 to 8 Years
- This position needs an individual contributor role with hands on work
- Development experience in BI/DW is must
- Understanding of dimensional and relational modelling
- Expertise in Azure Data Factory and DataBricks(Spark)
- Experience with data platform including but not limited to hands-on experience with data loading and transformations using Azure Data Factory.
- Expertise with Spark programming
- Expertise in ETL Design, development.
- Good understanding of architecture and design to meet functional and non-functional requirements
- Good understanding of Datalake, EDW, solution design artifacts, hosting solutions such as private/public cloud IaaS, PaaS and SaaS platforms.
- Experience in architecting and designing technical solutions for Microsoft-centric solutions based on industry standards using Azure IaaS, PaaS and SaaS capabilities.
- Experience with any of the following like unstructured data technologies such as SQL Server, Azure SQL, Azure Data Lake, DataBricks, HD Insights, Synapse, Hadoop, Cloudera, MongoDB, MySQL, Neo4j, Cassandra
- Experience with data ingestion technologies such as Azure Data Factory and Spark(Databricks) is must
- Software development full lifecycle methodologies, patterns, frameworks, libraries and tools
- Experience with CICD Process
- Hands on experience on Azure storage services like SQL DB, Tables, Files and Blobs
- Experience of executing cloud native projects in Azure with DevOps using VSTS along with Microsoft as well as
Power BI Developer
Experience: 6 to 8 Years
- Expert in Power BI development
- Background in data warehouse design (e.g. dimensional modeling) and data mining
- Good understanding Azure platform is plus
- Expertise in model development for reports
- In-depth understanding of database management systems, online analytical processing (OLAP) and ETL (Extract, transform, load) framework
- Familiarity with other BI technologies (e.g. Tableau or any other tool)
- Knowledge of SQL queries, SQL Server Integration Services (SSIS)/Azure Data factory
- Proven abilities to take initiative and be innovative
- Analytical mind with a problem-solving aptitude
- Leverage Power BI to pull data from other resources such as data lake
- Fine/Performance tuning of Power BI reports and dashboard
Experience:8 to 12 Years
- Experienced In Developing Solutions Focused On AWS and Big Data And Analytics Across Diverse Domains
- Has Led Enterprise Architecture And Solutioning Efforts To Define And Develop Big Data Components
- Deep Knowledge Of Best Practices Through Relevant Experience Across Data-Related Disciplines And
- Technologies, Particularly For Enterprise-Wide Data Architectures, Data Management, Data
- Governance And Data Warehousing
- Expertise In AWS Bigdata Platform, Cloudera Distribution
- Proficient In Building Large Scale Data Lake-Based Solutions using AWS
- Expertise In Streaming & Real-Time Data Processing using AWS
- Expertise In Data Modeling (Erwin, Rdbms & Nosql) & Data Virtualization (Denodo, Tibco)
- Expertise In Data Compression Techniques
- Expertise In Handling Pii Data.
- Proficient In Pyspark Framework
- Expertise In Nosql
- Expertise In Snowflake and Denodo
- Prior Experience In Big Data Implementations (Batch/Stream/Real-Time Processing), Elt/Etl And Hadoop
- Understanding Of Tools And Technologies Available Within The Enterprise Data & Analytics Ecosystem,
- With The Ability To Understand Functional Purpose Of Tools And Fit For A Specific Requirement
- Strong Capability To Drive The Project And Keeps Communication Clear Between Both Parties
- Own Technical Assessment, Drive And Manage It Implementation Plan, Governance And Progress Reporting
- Expertise In Agile Project Management Practices
Relevant retail Experience: 5 – 10 years
The person in this role is expected to perform the following activities on day to day basis:
lead teams from multiple sub-groups managing operations, client communications, teams, business development initiatives, and analytical solutions. In this role, the Manager will need to evaluate team members on their performance, troubleshoot typical analytical problems with the team, do hands-on deliveries and coding when team gets struck, and even back-fill for missing team-members during their long leaves or transitions. The person who will justify this role should be able to ramp-up fast on business and technology aspects, very articulate, innovative and should have a structured approach towards problem solving. Hands-on work- coding, dash-boarding, business presentations, analytical modelling should be regularly expected based on business requirements.
On the personal front, the person should be highly self-motivated, hard-working, articulate, passionate towards new solution building and able to lead, motivate, drive and at the same time handle multiple teams across subgroups and work with multiple stakeholders across legal, finance, pricing, marketing, and sales teams. Educational Criteria: Masters in Statistics/Mathematics/Economics/Econometric from Tier 1 institutions Or BE/B-Tech, MCA or MBA from Tier 1 institutions – Preferred
- Strong domain knowledge and thought leadership in retail domain (excl. Banks)
- The ideal candidate would be adept at understanding customer's business challenges and define appropriate analytics approach to design solution
- Should be able to convert mathematical/ statistics-based research/ academic literature into sustainable data science solutions
- Candidate should be able to think from first principles to define & evangelize solutions for any business problem
- This is a hands-on role and will be required to manage day to day delivery activities and guide the team in executing analytics projects by analyzing large volume of data
- Research and bring innovations to develop next generation solutions in core functional areas related to Promotion Effectiveness, Forecasting with detrending methods, Digital Marketing, Customer Relationship Management (CRM), Campaign Management & Data Insights etc
- Ideal candidate should have hands on experience on SQL, hive, Tableau/Qlik-view dashboard development, Statistical modelling, Machine Learning tools – R, python, AWS ML etc.
- Provide technical thought leadership, coaching and mentorship in the field of data science in working with engineering and other cross functional teams
- He / She would also be responsible for creating Business & technical presentations, reports etc. to present the analysis findings to the end clients and for business development
- This role requires excellent communication skills. Additionally, should also possess the ability to confidently socialize business recommendations and enable customer organization to execute such recommendations.
Technical Experience: (not all technical exposures are expected from one individual)
- Multiple linear regression, Logistic regression, ARIMA/ARIMAX
- Clustering, Decision Tree, Random Forest, Support Vector Machine, Naïve Bayes, GBM, PCA
- Optimization techniques (Single objective/multi objective), simulation, pymc3, GMM, GLM
- Recommender Systems (MF, ALS, Deep Learning) – collaborative/ content filtering
- Model automation and simulations, MMX, price elasticity models, CLTV, Assortment Optimization
- Sound understanding of mathematics like probability theory, differential calculus, Laplace and Furrier transformations etc
- Tools: R, Python, SQL, SAS, hyve, spark, big data, Experience in processing large amount of data using
- BigData technologies, Advanced knowledge of Excel and VBA, Knowledge of any visualization tools like Tableau, Spotfire, QlikView, Power BI etc.
Functional/Domain Experience: Retail Domain, E-Commerce
Google BigQuery Developer
Experience: 6 to 10 Years
- Industry experience building and productionizing data pipelines using dataflow
- Expertise in working complex SQL datasets.
- Expertise in building SQL scripts using BigQuery Syntax
- Performance tuning of BigQuery SQL scripts
- Experience in delivering artifacts such as scripts (Python), dataflow components Strong experience with SQL