Data Visualization

What You’ll Do:

 In-depth and strong knowledge of SQL.

- Basic knowledge of Java.

- Basic scripting knowledge.

- Strong analytical skills.

- Excellent debugging skills and problem-solving.

Who You Are:

- Comfortable working in EST+IST Timezone.

- Troubleshoot complex issues discovered in-house as well as in customer environments.

- Replicate customer environments/issues on Platform and Data and work to identify the root cause or provide interim workaround as needed.

- Ability to debug SQL queries associated with Data pipelines.

- Monitoring and debugging ETL job on a daily basis.

- Provide Technical Action plans to take a customer/product issue from start to resolution.

- Capture and document any Data incidents identified on Platform and maintain the history for such issues along with resolution.

- Identify product bugs and improvements based on customer environments and work to close them

- Ensure implementation/continuous improvement of formal processes to support product development activities.

- Good in external and internal communication across stakeholders.

Your key responsibilities

• Create and maintain optimal data pipeline architecture. Should have experience in building batch/real-time ETL Data Pipelines. Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources
• The individual will be responsible for solution design, integration, data sourcing, transformation, database design and implementation of complex data warehousing solutions.
• Responsible for development, support, maintenance, and implementation of a complex project module
• Provide expertise in area and advanced knowledge of applications programming and ensure application design adheres to the overall architecture blueprint
• Utilize advanced knowledge of system flow and develop standards for coding, testing, debugging, and implementation
• Resolve variety of high impact problems/projects through in-depth evaluation of complex business processes, system processes, and industry standards
• Continually improve ongoing reporting and analysis processes, automating or simplifying self-service support.
• complete reporting solutions.
• Preparation of HLD about architecture of the application and high level design.
• Preparation of LLD about job design, job description and in detail information of the jobs.
• Preparation of Unit Test cases and execution of the same.
• Provide technical guidance and mentoring to application development teams throughout all the phases of the software development life cycle

Skills and attributes for success

• Strong experience in SQL. Proficient in writing performant SQL working with large data volumes. Proficiency in writing and debugging complex SQLs.
• Strong experience in database system Microsoft Azure. Experienced in Azure Data Factory.
• Strong in Data Warehousing concepts. Experience with large-scale data warehousing architecture and data modelling.

• Should have enough experience to work on Power Shell Scripting

• Able to guide the team through the development, testing and implementation stages and review the completed work effectively
• Able to make quick decisions and solve technical problems to provide an efficient environment for project implementation
• Primary owner of delivery, timelines. Review code was written by other engineers.
• Maintain highest levels of development practices including technical design, solution development, systems configuration, test documentation/execution, issue identification and resolution, writing clean, modular and self-sustaining code, with repeatable quality and predictability
• Must have understanding of business intelligence development in the IT industry
• Outstanding written and verbal communication skills
• Should be adept in SDLC process - requirement analysis, time estimation, design, development, testing and maintenance
• Hands-on experience in installing, configuring, operating, and monitoring CI/CD pipeline tools
• Should be able to orchestrate and automate pipeline
• Good to have : Knowledge of distributed systems such as Hadoop, Hive, Spark

To qualify for the role, you must have

• Bachelor's Degree in Computer Science, Economics, Engineering, IT, Mathematics, or related field preferred
• More than 6 years of experience in ETL development projects
• Proven experience in delivering effective technical ETL strategies
• Microsoft Azure project experience
• Technologies: ETL- ADF, SQL, Azure components (must-have), Python (nice to have)

Ideally, you’ll also have

Company Profile:

The company is World's No1 Global management consulting firm.

Job Description

Function: Product → Product Analytics

Responsibilities:

• Assist product managers in the formulation of the company's product strategy using structured data and insights derived from the same
• Conduct research, create business cases and translate them into meaningful problems to solve
• Measure impact of experiments related to function, analysing and helping in course correction.
• Recommending product improvements based on analytical findings. Defining new metrics, techniques, and strategies to improve performance.
• Constantly monitor and analyse metrics identified, publish insights/any anomalies along with hypothesis
• Translating business requirements and user requests into effective report and dashboard designs in challenging deadlines.
• Assist with performance tuning of dashboards, background data queries as needed

Key Skills Required:

• Bachelor’s degree along with 2+ years experience in product analytics building data sets, reports, and dashboards
• Strong analytics skills and experience in Metabase, Google Analytics, Power BI, or other analytics software
• Proficiency with SQL
• Agile ability to anticipate need, be responsive and adapt to change
• Strong interpersonal and relationship skills, ability to influence decisions and gain consensus
• Excellent time and project management skills, ability to prioritise the most important projects to create business impact

Perks at Oneistox:

• Challenging work, High Product Ownership, and Steep Learning Curve are guaranteed!
• You get to be part of a highly young and energetic team.
• Envisage the growth of a company from 5X to 500X.
• Industry standard compensation and ESOPS.

Roles and Responsibilities

• Managing available resources such as hardware, data, and personnel so that deadlines are met.
• Analyzing the ML and Deep Learning algorithms that could be used to solve a given problem and ranking them by their success probabilities
• Exploring 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
• Defining validation framework and establish a process to ensure acceptable data quality criteria are met
• Supervising the data acquisition and partnership roadmaps to create stronger product for our customers.
• Defining feature engineering process to ensure usage of meaningful features given the business constraints which may vary by market
• Device self-learning strategies through analysis of errors from the models
• Understand business issues and context, devise a framework for solving unstructured problems and articulate clear and actionable solutions underpinned by analytics.
• Manage multiple projects simultaneously while demonstrating business leadership to collaborate & coordinate with different functions to deliver the solutions in a timely, efficient and effective manner.
• Manage project resources optimally to deliver projects on time; drive innovation using residual resources to create strong solution pipeline; provide direction, coaching & training, feedbacks to project team members to enhance performance, support development and encourage value aligned behaviour of the project team members; Provide inputs for periodic performance appraisal of project team members.

Preferred Technical & Professional expertise

• Undergraduate Degree in Computer Science / Engineering / Mathematics / Statistics / economics or other quantitative fields
• At least 2+ years of experience of managing Data Science projects with specializations in Machine Learning
• In-depth knowledge of cloud analytics tools.
• Able to drive Python Code optimization; ability review codes and provide inputs to improve the quality of codes
• Ability to evaluate hardware selection for running ML models for optimal performance
• Up to date with Python libraries and versions for machine learning; Extensive hands-on experience with Regressors; Experience working with data pipelines.
• Deep knowledge of math, probability, statistics and algorithms; Working knowledge of Supervised Learning, Adversarial Learning and Unsupervised learning
• Deep analytical thinking with excellent problem-solving abilities
• Strong verbal and written communication skills with a proven ability to work with all levels of management; effective interpersonal and influencing skills.
• Ability to manage a project team through effectively allocation of tasks, anticipating risks and setting realistic timelines for managing the expectations of key stakeholders
• Strong organizational skills and an ability to balance and handle multiple concurrent tasks and/or issues simultaneously.
• Ensure that the project team understand and abide by compliance framework for policies, data, systems etc. as per group, region and local standards

• Adept at Machine learning techniques and algorithms.

Feature selection, dimensionality reduction, building and

• optimizing classifiers using machine learning techniques
• Data mining using state-of-the-art methods
• Doing ad-hoc analysis and presenting results
• Proficiency in using query languages such as N1QL, SQL

Experience with data visualization tools, such as D3.js, GGplot,

• Plotly, PyPlot, etc.

Creating automated anomaly detection systems and constant tracking

• of its performance
• Strong in Python is a must.
• Strong in Data Analysis and mining is a must
• Deep Learning, Neural Network, CNN, Image Processing (Must)

Building analytic systems - data collection, cleansing and

• integration

Experience with NoSQL databases, such as Couchbase, MongoDB,

Cassandra, HBase

• 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