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JOB SUMMARY: The Senior Associate supports the Data Analytics Manager by proposing relevant analytics procedures/tools, executing the analytics and also developing visualization outputs for audits, continuous monitoring/auditing and IA initiatives. The individual’s responsibilities include -
Understanding audit and/or project objectives and assisting the manager in preparing the plan and timelines.
Working with the Process/BU/IA teams for gathering requirements for continuous monitoring/auditing projects.
Working with Internal audit project teams to understand the analytics requirements for audit engagements.
Independently build pilot/prototype, determine appropriate visual tool and design the views to meet project objectives.
Proficient in data management and data mining.
Highly skilled on visualization tools like Qlik View, Qlik Sense, Power BI, Tableau, Alteryx etc.
Working with Data Analytics Manager to develop analytics program aligned to the overall audit plan.
Showcasing analytics capability to Process management teams to increase adoption of continuous monitoring.
Establishing and maintaining relationships with all key stakeholders of internal audit.
Coaching other data analysts on analytics procedures, coding and tools.
Taking a significant and active role in developing and driving Internal Audit Data Analytics quality and knowledge sharing to enhance the value provided to Internal Audit stakeholders.
Ensuring timely and accurate time tracking.
Continuously focusing on self-development by attending trainings, seminars and acquiring relevant certifications.
Position Overview: We are seeking a talented Data Engineer with expertise in Power BI to join our team. The ideal candidate will be responsible for designing and implementing data pipelines, as well as developing insightful visualizations and reports using Power BI. Additionally, the candidate should have strong skills in Python, data analytics, PySpark, and Databricks. This role requires a blend of technical expertise, analytical thinking, and effective communication skills.
Key Responsibilities:
- Design, develop, and maintain data pipelines and architectures using PySpark and Databricks.
- Implement ETL processes to extract, transform, and load data from various sources into data warehouses or data lakes.
- Collaborate with data analysts and business stakeholders to understand data requirements and translate them into actionable insights.
- Develop interactive dashboards, reports, and visualizations using Power BI to communicate key metrics and trends.
- Optimize and tune data pipelines for performance, scalability, and reliability.
- Monitor and troubleshoot data infrastructure to ensure data quality, integrity, and availability.
- Implement security measures and best practices to protect sensitive data.
- Stay updated with emerging technologies and best practices in data engineering and data visualization.
- Document processes, workflows, and configurations to maintain a comprehensive knowledge base.
Requirements:
- Bachelor’s degree in Computer Science, Engineering, or related field. (Master’s degree preferred)
- Proven experience as a Data Engineer with expertise in Power BI, Python, PySpark, and Databricks.
- Strong proficiency in Power BI, including data modeling, DAX calculations, and creating interactive reports and dashboards.
- Solid understanding of data analytics concepts and techniques.
- Experience working with Big Data technologies such as Hadoop, Spark, or Kafka.
- Proficiency in programming languages such as Python and SQL.
- Hands-on experience with cloud platforms like AWS, Azure, or Google Cloud.
- Excellent analytical and problem-solving skills with attention to detail.
- Strong communication and collaboration skills to work effectively with cross-functional teams.
- Ability to work independently and manage multiple tasks simultaneously in a fast-paced environment.
Preferred Qualifications:
- Advanced degree in Computer Science, Engineering, or related field.
- Certifications in Power BI or related technologies.
- Experience with data visualization tools other than Power BI (e.g., Tableau, QlikView).
- Knowledge of machine learning concepts and frameworks.
Location: Chennai
Education: BE/BTech
Experience: Minimum 3+ years of experience as a Data Scientist/Data Engineer
Domain knowledge: Data cleaning, modelling, analytics, statistics, machine learning, AI
Requirements:
- To be part of Digital Manufacturing and Industrie 4.0 projects across client group of companies
- Design and develop AI//ML models to be deployed across factories
- Knowledge on Hadoop, Apache Spark, MapReduce, Scala, Python programming, SQL and NoSQL databases is required
- Should be strong in statistics, data analysis, data modelling, machine learning techniques and Neural Networks
- Prior experience in developing AI and ML models is required
- Experience with data from the Manufacturing Industry would be a plus
Roles and Responsibilities:
- Develop AI and ML models for the Manufacturing Industry with a focus on Energy, Asset Performance Optimization and Logistics
- Multitasking, good communication necessary
- Entrepreneurial attitude
Additional Information:
- Travel: Must be willing to travel on shorter duration within India and abroad
- Job Location: Chennai
- Reporting to: Team Leader, Energy Management System
at AxionConnect Infosolutions Pvt Ltd
Job Location: Hyderabad/Bangalore/ Chennai/Pune/Nagpur
Notice period: Immediate - 15 days
1. Python Developer with Snowflake
Job Description :
- 5.5+ years of Strong Python Development Experience with Snowflake.
- Strong hands of experience with SQL ability to write complex queries.
- Strong understanding of how to connect to Snowflake using Python, should be able to handle any type of files
- Development of Data Analysis, Data Processing engines using Python
- Good Experience in Data Transformation using Python.
- Experience in Snowflake data load using Python.
- Experience in creating user-defined functions in Snowflake.
- Snowsql implementation.
- Knowledge of query performance tuning will be added advantage.
- Good understanding of Datawarehouse (DWH) concepts.
- Interpret/analyze business requirements & functional specification
- Good to have DBT, FiveTran, and AWS Knowledge.
About the company:
VakilSearch is a technology-driven platform, offering services that cover the legal needs of startups and established businesses. Some of our services include incorporation, government registrations & filings, accounting, documentation and annual compliances. In addition, we offer a wide range of services to individuals, such as property agreements and tax filings. Our mission is to provide one-click access to individuals and businesses for all their legal and professional needs.
You can learn more about us at https://vakilsearch.com/">vakilsearch.com.
About the role:
A successful data analyst needs to have a combination of technical as well leadership skills. A background in Mathematics, Statistics, Computer Science, Information Management can serve as a solid foundation to build your career as a data analyst at VakilSearch.
Why to join Vakilsearch:
- Unlimited opportunities to grow
- Flat hierarchy
- Encouraging environment to unleash your out of box thinking skills
Responsibilities:
- Preparing reports for the stakeholders and the management, enabling them to take important decisions based on various facts and trends.
- Using automated tools to extract data from primary and secondary sources
- Identify and recommend the right product metrics to be analysed and tracked for every feature/problem statement.
- Using statistical tools to identify, analyze, and interpret patterns and trends in complex data sets that could be helpful for the diagnosis and prediction
- Working with programmers, engineers, and management heads to identify process improvement opportunities, propose system modifications, and devise data governance strategies.
Required skills:
- Bachelor’s degree from an accredited university or college in computer science or graduate from data science related program
- Minimum of 0 - 2 years experience in analysing
Responsibilities:
- Be the analytical expert in Kaleidofin, managing ambiguous problems by using data to execute sophisticated quantitative modeling and deliver actionable insights.
- Develop comprehensive skills including project management, business judgment, analytical problem solving and technical depth.
- Become an expert on data and trends, both internal and external to Kaleidofin.
- Communicate key state of the business metrics and develop dashboards to enable teams to understand business metrics independently.
- Collaborate with stakeholders across teams to drive data analysis for key business questions, communicate insights and drive the planning process with company executives.
- Automate scheduling and distribution of reports and support auditing and value realization.
- Partner with enterprise architects to define and ensure proposed.
- Business Intelligence solutions adhere to an enterprise reference architecture.
- Design robust data-centric solutions and architecture that incorporates technology and strong BI solutions to scale up and eliminate repetitive tasks.
- Experience leading development efforts through all phases of SDLC.
- 2+ years "hands-on" experience designing Analytics and Business Intelligence solutions.
- Experience with Quicksight, PowerBI, Tableau and Qlik is a plus.
- Hands on experience in SQL, data management, and scripting (preferably Python).
- Strong data visualisation design skills, data modeling and inference skills.
- Hands-on and experience in managing small teams.
- Financial services experience preferred, but not mandatory.
- Strong knowledge of architectural principles, tools, frameworks, and best practices.
- Excellent communication and presentation skills to communicate and collaborate with all levels of the organisation.
- Preferred candidates with less than 30 days notice period.
Senior Software Engineer
MUST HAVE:
POWER BI with PLSQL
experience: 5+ YEARS
cost: 18 LPA
WHF- HYBRID
- Building and operationalizing large scale enterprise data solutions and applications using one or more of AZURE data and analytics services in combination with custom solutions - Azure Synapse/Azure SQL DWH, Azure Data Lake, Azure Blob Storage, Spark, HDInsights, Databricks, CosmosDB, EventHub/IOTHub.
- Experience in migrating on-premise data warehouses to data platforms on AZURE cloud.
- Designing and implementing data engineering, ingestion, and transformation functions
- Experience with Azure Analysis Services
- Experience in Power BI
- Experience with third-party solutions like Attunity/Stream sets, Informatica
- Experience with PreSales activities (Responding to RFPs, Executing Quick POCs)
- Capacity Planning and Performance Tuning on Azure Stack and Spark.
We are looking for an outstanding ML Architect (Deployments) with expertise in deploying Machine Learning solutions/models into production and scaling them to serve millions of customers. A candidate with an adaptable and productive working style which fits in a fast-moving environment.
Skills:
- 5+ years deploying Machine Learning pipelines in large enterprise production systems.
- Experience developing end to end ML solutions from business hypothesis to deployment / understanding the entirety of the ML development life cycle.
- Expert in modern software development practices; solid experience using source control management (CI/CD).
- Proficient in designing relevant architecture / microservices to fulfil application integration, model monitoring, training / re-training, model management, model deployment, model experimentation/development, alert mechanisms.
- Experience with public cloud platforms (Azure, AWS, GCP).
- Serverless services like lambda, azure functions, and/or cloud functions.
- Orchestration services like data factory, data pipeline, and/or data flow.
- Data science workbench/managed services like azure machine learning, sagemaker, and/or AI platform.
- Data warehouse services like snowflake, redshift, bigquery, azure sql dw, AWS Redshift.
- Distributed computing services like Pyspark, EMR, Databricks.
- Data storage services like cloud storage, S3, blob, S3 Glacier.
- Data visualization tools like Power BI, Tableau, Quicksight, and/or Qlik.
- Proven experience serving up predictive algorithms and analytics through batch and real-time APIs.
- Solid working experience with software engineers, data scientists, product owners, business analysts, project managers, and business stakeholders to design the holistic solution.
- Strong technical acumen around automated testing.
- Extensive background in statistical analysis and modeling (distributions, hypothesis testing, probability theory, etc.)
- Strong hands-on experience with statistical packages and ML libraries (e.g., Python scikit learn, Spark MLlib, etc.)
- Experience in effective data exploration and visualization (e.g., Excel, Power BI, Tableau, Qlik, etc.)
- Experience in developing and debugging in one or more of the languages Java, Python.
- Ability to work in cross functional teams.
- Apply Machine Learning techniques in production including, but not limited to, neuralnets, regression, decision trees, random forests, ensembles, SVM, Bayesian models, K-Means, etc.
Roles and Responsibilities:
Deploying ML models into production, and scaling them to serve millions of customers.
Technical solutioning skills with deep understanding of technical API integrations, AI / Data Science, BigData and public cloud architectures / deployments in a SaaS environment.
Strong stakeholder relationship management skills - able to influence and manage the expectations of senior executives.
Strong networking skills with the ability to build and maintain strong relationships with both business, operations and technology teams internally and externally.
Provide software design and programming support to projects.
Qualifications & Experience:
Engineering and post graduate candidates, preferably in Computer Science, from premier institutions with proven work experience as a Machine Learning Architect (Deployments) or a similar role for 5-7 years.