Insurance Information Bureau - Data Engineer - ETL/Data Pipeline (4-5 yrs)

Location : Hyderabad, India

Reporting Manager : Head of Analytics

Work Pattern : Full Time, 5 days in the office

- Minimum Experience as a data engineer: 4-5 years

- Uses expertise in data engineering and programming to build systems that collect, manage and convert raw data into usable information for data analysts, data scientists and business analysts.

- Construct datasets that are easy to analyse and support company requirements.

- Combine raw information from different sources to create consistent and machine-readable formats.

- Develop and test architectures that enable data extraction and transformation for predictive or prescriptive modeling.

Responsibilities :

- Designing and building optimized data pipelines using cutting-edge technologies in a cloud environment to drive analytical insights

- Constructing infrastructure for efficient ETL and ELT processes from various sources and storage systems

- Knowledge of how to create and improve data sets, "big data" data pipelines, and infrastructures

- Being able to do root cause analysis on data and procedures both internally and outside to find possibilities for improvement and provide clarification

- Outstanding analytical abilities related to coping with unstructured datasets.

- Capacity to develop procedures that support task management, data structures, dependence, and metadata

- Strong project management and organisational skills

- Collaborating closely with Product Managers and Business Managers to design technical solutions aligned with business requirements

- Leading the implementation of algorithms and prototypes to transform raw data into useful information

- Architecting, designing, and maintaining database pipeline architectures, ensuring readiness for AI/ML transformations

- Creating innovative data validation methods and data analysis tools

- Ensuring compliance with data governance and security policies

- Interpreting data trends and patterns to establish operational alerts

- Developing analytical tools, programs, and reporting mechanisms

- Conducting complex data analysis and presenting results effectively

- Preparing data for prescriptive and predictive modeling

- Continuously exploring opportunities to enhance data quality and reliability

- Applying strong programming and problem-solving skills to develop scalable solutions

- Collaborate with data scientists, data analysts and architects on several products and projects

Skills

- 4+ years of hands-on experience designing, building, deploying, testing, maintaining, monitoring, and owning scalable, resilient, and distributed data pipelines

- Technical expertise with data models, data mining, and segmentation techniques for both structured and unstructured data

- High proficiency in Scala/Java and Spark for applied large-scale data processing

- Expertise with big data technologies, including Spark, Data Lake, Delta Lake, and Hive

- Solid understanding of batch and streaming data processing techniques

- Proficient knowledge of the Data Lifecycle Management process, including data collection, access, use, storage, transfer, and deletion

- Expert-level ability to write complex, optimized SQL queries across extensive data volumes

- Experience with RDBMS and OLAP databases like MySQL, Redshift

- Familiarity with Hadoop, HBase, MapReduce, and other suitable platforms.

- Excellent understanding of operating systems like UNIX, Linux, and Windows

- Familiarity with Agile methodologies

- Obsession for service observability, instrumentation, monitoring, and alerting

- Knowledge or experience in architectural best practices for building data lakes

- Hands-on data management in any of the hyperscalers - Azure, AWS, GCP

Good to Have :

- Passion for testing strategy, problem-solving, and continuous learning.

- Willingness to acquire new skills and knowledge

- Possess a product/engineering mindset to drive impactful data solutions

- Experience working in distributed environments with global teams

- Great numerical and analytical skills

Soft Skills :

- Analytical thinking skills

- Excellent verbal and written communication skills

- Problem-solving skills

Tools and Programs (Min 3 of these) : Python, SQL, Databricks, Kedro, Airflow, Luigi, PowerBI, Tableau, Java, C#

Education :

- A bachelor's degree in computer science, data science, statistics or related field.

- A master's degree in data management, information science or similar is preferred.

- Certifications from IBM, Google