11+ KDB Jobs in Bangalore (Bengaluru) | KDB Job openings in Bangalore (Bengaluru)

Job Description

The applicant must have a minimum of 5 years of hands-on IT experience, working on a full software lifecycle in Agile mode.

Good to have experience in data modeling and/or systems architecture.
Responsibilities will include technical analysis, design, development and perform enhancements.

You will participate in all/most of the following activities:
- Working with business analysts and other project leads to understand requirements.
- Modeling and implementing database schemas in DB2 UDB or other relational databases.
- Designing, developing, maintaining and Data processing using Python, DB2, Greenplum, Autosys and other technologies

Skills /Expertise Required :

Work experience in developing large volume database (DB2/Greenplum/Oracle/Sybase).

Good experience in writing stored procedures, integration of database processing, tuning and optimizing database queries.

Strong knowledge of table partitions, high-performance loading and data processing.
Good to have hands-on experience working with Perl or Python.
Hands on development using Spark / KDB / Greenplum platform will be a strong plus.
Designing, developing, maintaining and supporting Data Extract, Transform and Load (ETL) software using Informatica, Shell Scripts, DB2 UDB and Autosys.
Coming up with system architecture/re-design proposals for greater efficiency and ease of maintenance and developing software to turn proposals into implementations.

Need to work with business analysts and other project leads to understand requirements.
Strong collaboration and communication skills

- Modeling complex problems, discovering insights, and identifying opportunities through the use of statistical, algorithmic, mining, and visualization techniques

- Experience working with business understanding the requirement, creating the problem statement, and building scalable and dependable Analytical solutions

- Must have hands-on and strong experience in Python

- Broad knowledge of fundamentals and state-of-the-art in NLP and machine learning

- Strong analytical & algorithm development skills

- Deep knowledge of techniques such as Linear Regression, gradient descent, Logistic Regression, Forecasting, Cluster analysis, Decision trees, Linear Optimization, Text Mining, etc

- Ability to collaborate across teams and strong interpersonal skills

Skills

- Sound theoretical knowledge in ML algorithm and their application

- Hands-on experience in statistical modeling tools such as R, Python, and SQL

- Hands-on experience in Machine learning/data science

- Strong knowledge of statistics

- Experience in advanced analytics / Statistical techniques – Regression, Decision trees, Ensemble machine learning algorithms, etc

- Experience in Natural Language Processing & Deep Learning techniques 

- Pandas, NLTK, Scikit-learn, SpaCy, Tensorflow

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.

Job Title: Data Engineer

Job Summary: As a Data Engineer, you will be responsible for designing, building, and maintaining the infrastructure and tools necessary for data collection, storage, processing, and analysis. You will work closely with data scientists and analysts to ensure that data is available, accessible, and in a format that can be easily consumed for business insights.

Responsibilities:

• Design, build, and maintain data pipelines to collect, store, and process data from various sources.
• Create and manage data warehousing and data lake solutions.
• Develop and maintain data processing and data integration tools.
• Collaborate with data scientists and analysts to design and implement data models and algorithms for data analysis.
• Optimize and scale existing data infrastructure to ensure it meets the needs of the business.
• Ensure data quality and integrity across all data sources.
• Develop and implement best practices for data governance, security, and privacy.
• Monitor data pipeline performance / Errors and troubleshoot issues as needed.
• Stay up-to-date with emerging data technologies and best practices.

Requirements:

Bachelor's degree in Computer Science, Information Systems, or a related field.

Experience with ETL tools like Matillion,SSIS,Informatica

Experience with SQL and relational databases such as SQL server, MySQL, PostgreSQL, or Oracle.

Experience in writing complex SQL queries

Strong programming skills in languages such as Python, Java, or Scala.

Experience with data modeling, data warehousing, and data integration.

Strong problem-solving skills and ability to work independently.

Excellent communication and collaboration skills.

Familiarity with big data technologies such as Hadoop, Spark, or Kafka.

Familiarity with data warehouse/Data lake technologies like Snowflake or Databricks

Familiarity with cloud computing platforms such as AWS, Azure, or GCP.

Familiarity with Reporting tools

Teamwork/ growth contribution

• Helping the team in taking the Interviews and identifying right candidates
• Adhering to timelines
• Intime status communication and upfront communication of any risks
• Tech, train, share knowledge with peers.
• Good Communication skills
• Proven abilities to take initiative and be innovative
• Analytical mind with a problem-solving aptitude

Good to have :

Master's degree in Computer Science, Information Systems, or a related field.

Experience with NoSQL databases such as MongoDB or Cassandra.

Familiarity with data visualization and business intelligence tools such as Tableau or Power BI.

Knowledge of machine learning and statistical modeling techniques.

If you are passionate about data and want to work with a dynamic team of data scientists and analysts, we encourage you to apply for this position.

• 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

1. Data Steward :

Data Steward will collaborate and work closely within the group software engineering and business division. Data Steward has overall accountability for the group's / Divisions overall data and reporting posture by responsibly managing data assets, data lineage, and data access, supporting sound data analysis. This role requires focus on data strategy, execution, and support for projects, programs, application enhancements, and production data fixes. Makes well-thought-out decisions on complex or ambiguous data issues and establishes the data stewardship and information management strategy and direction for the group. Effectively communicates to individuals at various levels of the technical and business communities. This individual will become part of the corporate Data Quality and Data management/entity resolution team supporting various systems across the board.

Primary Responsibilities:

• Responsible for data quality and data accuracy across all group/division delivery initiatives.
• Responsible for data analysis, data profiling, data modeling, and data mapping capabilities.
• Responsible for reviewing and governing data queries and DML.
• Accountable for the assessment, delivery, quality, accuracy, and tracking of any production data fixes.
• Accountable for the performance, quality, and alignment to requirements for all data query design and development.
• Responsible for defining standards and best practices for data analysis, modeling, and queries.
• Responsible for understanding end-to-end data flows and identifying data dependencies in support of delivery, release, and change management.
• Responsible for the development and maintenance of an enterprise data dictionary that is aligned to data assets and the business glossary for the group responsible for the definition and maintenance of the group's data landscape including overlays with the technology landscape, end-to-end data flow/transformations, and data lineage.
• Responsible for rationalizing the group's reporting posture through the definition and maintenance of a reporting strategy and roadmap.
• Partners with the data governance team to ensure data solutions adhere to the organization’s data principles and guidelines.
• Owns group's data assets including reports, data warehouse, etc.
• Understand customer business use cases and be able to translate them to technical specifications and vision on how to implement a solution.
• Accountable for defining the performance tuning needs for all group data assets and managing the implementation of those requirements within the context of group initiatives as well as steady-state production.
• Partners with others in test data management and masking strategies and the creation of a reusable test data repository.
• Responsible for solving data-related issues and communicating resolutions with other solution domains.
• Actively and consistently support all efforts to simplify and enhance the Clinical Trial Predication use cases.
• Apply knowledge in analytic and statistical algorithms to help customers explore methods to improve their business.
• Contribute toward analytical research projects through all stages including concept formulation, determination of appropriate statistical methodology, data manipulation, research evaluation, and final research report.
• Visualize and report data findings creatively in a variety of visual formats that appropriately provide insight to the stakeholders.
• Achieve defined project goals within customer deadlines; proactively communicate status and escalate issues as needed.

Additional Responsibilities:

• Strong understanding of the Software Development Life Cycle (SDLC) with Agile Methodologies
• Knowledge and understanding of industry-standard/best practices requirements gathering methodologies.
• Knowledge and understanding of Information Technology systems and software development.
• Experience with data modeling and test data management tools.
• Experience in the data integration project • Good problem solving & decision-making skills.
• Good communication skills within the team, site, and with the customer

Knowledge, Skills and Abilities

• Technical expertise in data architecture principles and design aspects of various DBMS and reporting concepts.
• Solid understanding of key DBMS platforms like SQL Server, Azure SQL
• Results-oriented, diligent, and works with a sense of urgency. Assertive, responsible for his/her own work (self-directed), have a strong affinity for defining work in deliverables, and be willing to commit to deadlines.
• Experience in MDM tools like MS DQ, SAS DM Studio, Tamr, Profisee, Reltio etc.
• Experience in Report and Dashboard development
• Statistical and Machine Learning models
• Python (sklearn, numpy, pandas, genism)
• Nice to Have:
• 1yr of ETL experience
• Natural Language Processing
• Neural networks and Deep learning
• xperience in keras,tensorflow,spacy, nltk, LightGBM python library

Interaction :  Frequently interacts with subordinate supervisors.

Education : Bachelor’s degree, preferably in Computer Science, B.E or other quantitative field related to the area of assignment. Professional certification related to the area of assignment may be required

Experience :  7 years of Pharmaceutical /Biotech/life sciences experience, 5 years of Clinical Trials experience and knowledge, Excellent Documentation, Communication, and Presentation Skills including PowerPoint

• Use data to develop machine learning models that optimize decision making in Credit Risk, Fraud, Marketing, and Operations
• Implement data pipelines, new features, and algorithms that are critical to our production models
• Create scalable strategies to deploy and execute your models
• Write well designed, testable, efficient code
• Identify valuable data sources and automate collection processes.
• Undertake to preprocess of structured and unstructured data.
• Analyze large amounts of information to discover trends and patterns.

Requirements:

• 2+ years of experience in applied data science or engineering with a focus on machine learning
• Python expertise with good knowledge of machine learning libraries, tools, techniques, and frameworks (e.g. pandas, sklearn, xgboost, lightgbm, logistic regression, random forest classifier, gradient boosting regressor, etc)
• strong quantitative and programming skills with a product-driven sensibility