Engineer jobs in India

This Legal Counsel role in Bengaluru is an excellent opportunity for a qualified legal professional to provide expert legal advisory and compliance support. The role requires a detail-oriented individual with strong expertise in M&A, PE/VC transactions and general corporate advisory.

This is a senior-level talent acquisition and strategy role supporting multiple verticals including investment banking, venture capital, public equities, and the founder's office. The role focuses on end-to-end hiring, market intelligence, pipeline development, and culture shaping. Candidates must bring 8+ years of experience in IB/VC/PE or executive search, with a strong drive to build high-performing teams.

The role of Technical Head - L&D involves leading the design, development, and implementation of learning and development strategies in the Quality Engineering (QE) and digital transformation enabling firm. This position is based in Navi Mumbai and requires expertise in driving technical training initiatives to enhance workforce capabilities.

Qualifications & Required Skills: Full-Time

bachelor's or master's degree in engineering/technology, computer science, information technology, or related fields.

 10+ years of total experience in data modeling and database design and experience in Retail domain will be added advantage.

 8+ years of experience in data engineering development and support.

 3+ years of experience in leading technical team of data engineers and BI engineers  Proficiency in data modeling tools such as Erwin, ER/Studio, or similar tools.

 Strong knowledge of Azure cloud infrastructure and development using SQL/Python/PySpark using ADF, Synapse and Databricks.

 Hands-on experience with Azure Data Factory, Azure Synapse Analytics, Azure Analysis Services, Azure Databricks, Blob Storage, Python/PySpark, Logic Apps, Key Vault, and Azure functions.

 Strong communication, interpersonal, collaboration skills along with leadership capabilities.

 Ability to work effectively in a fast-paced, dynamic environment as cloud SME.

 Act as single point of contact for all kinds of data management related queries to make data decisions.

 Design and manage centralized, end-to-end data architecture solutions, such as- Data model designs, Database development standards, Implementation and management of data warehouses, Data analytics systems.

 Conduct continuous audits of data management system performance and refine where necessary.

 Identify bottlenecks, optimize queries, and implement caching mechanisms to enhance data processing speed.

 Work to integrate disparate data sources, including internal databases and external application programming interfaces (APIs), enabling organizations to derive insights from a holistic view of the data.

 Ensure data privacy measures comply with regulatory standards.Preferred

* Azure Data Factory (ADF), Databricks certification is a plus.

* Data Architect or Azure cloud Solution Architect certification is a plus.Technologies we use: Azure Data Factory, Databricks, Azure Synapse, Azure Tabular, Azure Functions, Logic Apps, Key Vault, DevOps, Python, PySpark, Scripting (PowerShell, Bash), Git, Terraform, Power BI, Snowflake

YOUR RESPONSIBILITIES:

• Design and Develop Applications: Build robust and scalable software solutions that align with business, security, and compliance requirements.
• Transform Legacy Systems: Understand legacy applications while leading their migration to modern cloud platforms.
• Implement Clean Architecture & DDD: Design and develop software adhering to best practices, ensuring scalability and maintainability.
• Collaborate with Teams: Work closely with the Requirements Engineer, Experts, and other stakeholders to translate technical specifications into working software solutions.
• Develop with Quality in Mind: Apply test-driven development (TDD) and integrate testing seamlessly into the development process.
• Support Integration & Maintenance: Contribute to integration, testing, deployment, and maintenance by correcting errors and adding enhancements.
• Drive Continuous Integration & Deployment (CI/CD): Continuously integrate and deploy applications to ensure streamlined development and delivery.
• Innovate Software Engineering Methods: Research, develop, and implement new software engineering techniques to enhance efficiency and effectiveness.
• Refine Development Processes: Establish and improve processes, standards, and guidelines for software development to ensure high-quality outputs.

WHAT WE ARE LOOKING FOR

Technical:

• Programming Languages: Java 8 & 11, Java 17, Spring Boot.
• Cloud Platforms: Experience migrating applications to AWS.
• Containerization: Experience with Docker.
• Strong experience with Maven.
• Architectural Principles: Proficiency in Clean Architecture and Domain-Driven Design (DDD).
• Development Practices: Test-Driven Development (TDD), Continuous Integration (CI), and Continuous Deployment (CD).
• Problem-Solving Skills: Strong debugging, troubleshooting, and performance optimization abilities.

Personal:

• Experience: 7+ years in technology, particularly in trending technologies.
• Software Development: At least 7 years of experience in design and development, with experience in large multinational organizations preferred.
• Communication: Excellent collaboration, communication, and analytical skills.
• Proactive: A focus on cost reduction, automation, and process efficiency improvements.
• Team Player: Ability to work independently and as part of a team.
• Motivation & Energy: High-energy individual, capable of motivating teams and fostering collaboration.

Qualifications

 Bachelor's degree in computer engineering, Computer Science, Data Analytics, or related field.

 3-4 years of experience in BI engineering or data analytics and advanced SQL Programming like PL/SQL.  Strong hands-on experience with Microsoft Power BI (including Power Query, DAX, dataflows, etc.).  In-depth knowledge of report design, development and maintenance, data extraction from DWH and cubes layer and dimensional data modeling concepts.  Strong hands-on experience with Python/Spark scripting and shell (Unix/Linux) scripting.  Familiarity with data warehousing concepts and cloud data platforms (Azure, Snowflake, etc.) and their services like Azure Synapse Analytics, Azure Analysis Services, Azure Databricks, Azure SQL DW/Synapse.  Excellent communication and stakeholder management skills with Strong analytical abilities.  Self-starter and motivated with ability to work in a fast-paced development environment.  Proficiency in the development environment, including IDE, database server, GIT, Continuous Integration, unit-testing tool, and defect management tools.Responsibilities:

* Design, develop, and deploy Power BI dashboards, reports, and data models. * Support and monitor the existing reports in maintenance with clear documentation. * Optimize DAX queries and Power BI performance for scalability and responsiveness. * Automate the existing reports by removing manual steps and adhere reporting best practices. * Supports in analyzing reports, admin activities, usage monitoring, and licensing costs optimization. * Write custom scripts to extract data from unstructured/semi-structured sources from data warehouse or BI Cubes or from Snowflake. * Skilled in dashboard deployment, report consolidation, and enhancing report usability for end users. * Work with data engineers to define and validate data from the data sources for Power BI consumption. * Collaborate with business stakeholders to define KPIs and build self-service BI tools. * Proactive and clear communication about the report status with the stakeholders. * Provide Power BI training, support, and up to date documentation for business users and conduct KT sessions for the junior resources to guide and mentor themPreferred Skills:

* Microsoft Certified: Data Analyst Associate or equivalent Power BI certification. * Hands-on experience with Microsoft Power BI (including Power Query, DAX, dataflows, etc.). * Basic understanding of reporting governance and Power BI administration. * Working Knowledge of Dev-Ops processes (CI/CD), Azure DevOps, Git/Jenkins version control tool, reporting and maintenance of BI reports and SQL scripting. * Hands-on experience in extracting data from databases like (Azure SQL DB, MySQL/, Cosmos DB etc.), SharePoint, Python/Unix shell Scripting. Technologies we use: Power BI, Databricks, Python, PySpark, Scripting (Power shell, Bash), Azure SQL DW/Synapse, Azure Tabular/Cubes, Azure DevOps, Git, Terraform, Snowflake

Data Scientist (IT)Position:

Data ScientistJob type:

Techno-FunctionalPreferred education qualifications:

Bachelor/ Master's degree in Statistics, Operation Research, Computer Science, Data Science OR related quantitative fieldJob location:

IndiaGeography:

SAPMENARequired experience:

6-8 YearsPreferred profile/ skills:



§ 5+ years in developing and implementing forecasting models

§ [Mandatory] Proven track record in data analysis (EDA, profiling, sampling), data engineering (wrangling, storage, pipelines, orchestration)

§ [Mandatory] Proven expertise in time series analysis, regression analysis, and other statistical modelling techniques

§ [Mandatory] Experience in ML algorithms such as ARIMA, Prophet, Random Forests, and Gradient Boosting algorithms (XGBoost, LightGBM, CatBoost)

§ [Mandatory] Experience in model explainability with Shapley plot and data drift detection metrics.

§ [Mandatory] Strong programming & analysis skills with Python and SQL, including experience with relevant forecasting packages

§ [Mandatory] Prior experience on Data Science & ML Engineering on Google Cloud

§ [Mandatory] Proficiency in version control systems such as GitHub

§ [Mandatory] Strong organizational capabilities; and ability to work in a matrix/ multidisciplinary team

§ [Mandatory] Excellent communication and presentation skills, with the ability to explain complex technical concepts to non-technical audience

§ Experience in Beauty or Retail/FMCG industry is preferred

§ Experience in handling large volume of data (>100 GB)

§ Experience in delivering AI-ML projects using Agile methodologies is preferred

§ Proven ability to work proactively and independently to address product requirements and design optimal solutionsJob objectives:

Design, develop, implement, and maintain data science and machine learning solutions to meet enterprise goals. Collaborate with cross-functional teams to leverage statistical modeling, machine learning, and data mining techniques to improve forecast accuracy and aid strategic decision-making across the organization. Scale the proven AI-ML Product across the SAPMENA region.Job description:§ Deep understanding of business/functional needs, problem statements and objectives/success criteria

§ Develop and maintain sophisticated statistical forecasting models, incorporating factors such as seasonality, promotions, media, traffic and other economic indicators

§ Collaborate with internal and external stakeholders including business, data scientists & product team to understand the business and product needs and translate them into actionable data-driven solutions

§ Review MVP implementations, provide recommendations and ensure Data Science best practices and guidelines are followed

§ Evaluate and compare the performance of different forecasting models, recommending optimal approaches for various business scenarios

§ Analyze large and complex datasets to identify patterns, insights, and potential risks and opportunities

§ Communicate forecasting results and insights to both technical and non-technical audiences through clear visualizations and presentations

§ Stay up to date with the latest advancements in forecasting techniques and technologies, continuously seeking opportunities for improvement

§ Contribute to the development of a robust data infrastructure for AI-ML solutions, ensuring data quality and accessibility

§ Collaborate with other data scientists and engineers to build and deploy scalable AI-ML solutions

Job RequirementsEducation

* Bachelor's degree required, preferably with a quantitative focus (Statistics, Business Analytics, Data Science, Math, Economics, etc.)

* Master's degree preferred (MBA/MS Computer Science/M.Tech Computer Science, etc.)Relevant Experience

* 5 - 7 years for Data Scientist

* Relevant working experience in a data science/advanced analytics roleBehavioural Skills

* Delivery Excellence

* Business disposition

* Social intelligence

* Innovation and agilityExperience

* Functional Analytics (Supply chain analytics, Marketing Analytics, Customer Analytics, etc.)

* Statistical modelling using Analytical tools (R, Python, KNIME, etc.)

* Knowledge of statistics and experimental design (A/B testing, hypothesis testing, causal inference)

* Practical experience building scalable ML models, feature engineering, model evaluation metrics, and statistical inference.

* Practical experience deploying models using MLOps tools and practices (e.g., MLflow, DVC, Docker, etc.)

* Strong coding proficiency in Python (Pandas, Scikit-learn, PyTorch/TensorFlow, etc.)

* Big data technologies & framework (AWS, Azure, GCP, Hadoop, Spark, etc.)

* Enterprise reporting systems, relational (MySQL, Microsoft SQL Server etc.), non-relational (MongoDB, DynamoDB) database management systems and Data Engineering tools

* Business intelligence & reporting (Power BI, Tableau, Alteryx, etc.)

* Microsoft Office applications (MS Excel, etc.)Roles & Responsibilities

Analytics & Strategy

1. Analyse large-scale structured and unstructured data; develop deep-dive analyses and machine learning models in retail, marketing, merchandising, and other areas of the business

2. Utilize data mining, statistical and machine learning techniques to derive business value from store, product, operations, financial, and customer transactional data

3. Apply multiple algorithms or architectures and recommend the best model with in-depth description to evangelize data-driven business decisions

4. Utilize cloud setup to extract processed data for statistical modelling and big data analysis, and visualization tools to represent large sets of time series/cross-sectional dataOperational Excellence

1. Follow industry standards in coding solutions and follow programming life cycle to ensure standard practices across the project

2. Structure hypothesis, build thoughtful analyses, develop underlying data models and bring clarity to previously undefined problems

3. Partner with Data Engineering to build, design and maintain core data infrastructure, pipelines and data workflows to automate dashboards and analysesStakeholder Engagement

1. Working collaboratively across multiple sets of stakeholders - Business functions, Data Engineers, Data Visualization experts to deliver on project deliverables

2. Articulate complex data science models to business teams and present the insights in easily understandable and innovative formats