Senior Data Analyst - ETL/Python

Description Analyze data using statistical models that drive product strategy and make data informed decisions, while designing and maintaining data pipelines. Collect requirements and collaborate with agencies, system integrators, solution providers, and other data sources to integrate relevant datasets into in house products.Qualification : B.E./B.Tech in CSE/ECEDomain : IoT, Big Data, GISSkills Python (NumPy, pandas) for data cleaning, transformation, and numerical computing. Exploratory Data Analysis (EDA) with visualization using Matplotlib and Plotly. Statistical analysis and hypothesis testing for data-driven insights. Solid understanding of descriptive statistics and inferential analysis on data. REST API integration for data ingestion and application development. Solid understanding of available data sources and APIs, including the ability to evaluate data quality, availability frequency, and common issues like data stream repetitions, as well as familiarity with various data fields and their meanings, and data structure formats (JSON, GeoJSON). Strong command of data visualization best practices for clear, actionable dashboards and plots. Proficient in Linux, with experience in GIT version control and cloud computing platforms. Strong understanding of IoT, GIS, Big Data, and Cloud applications aimed at improving operational efficiency and service delivery, with a commitment to creating a positive societal impact. Experience in containerization using Docker, with familiarity in Kubernetes for orchestration is a plus. Knowledge of monitoring and logging tools such as Prometheus, Grafana, and Logstash would be a strong plus.Responsibilities Evaluate APIs and datasets, create data models, develop software ETL modules, perform unit testing, and deploy them in cloud environments. Develop ETL modules in Python to ingest data into data exchange using REST APIs and streaming protocols such as AMQP and MQTT. This includes containerizing the adapters, creating data models, and catalogue entries according to data exchange specifications. Follow best practices for software development and adhere to Agile methodology throughout.(ref:hirist.tech)