Senior Data Engineer (7-11 yrs)

Key Responsibilities :

- Lead and drive discovery sessions with external clients and build state-of-the-art data architectures.

- Work with stakeholders to understand their problem statements, data requirements and implement solutions that meet their needs.

- Design, implement, and develop data pipelines to collect and process large amounts of data from various sources.

- Implement data storage solutions that are scalable, secure, and efficient, such as data warehouses and databases.

- Develop and implement data validation and testing processes to ensure that data is processed accurately and efficiently.

- Automate data collection, processing, and reporting processes to minimize manual work and improve efficiency.

- Create high quality documents to capture problem statements, requirements, solutions and designs.

- Support pre-sales activities, including whiteboard sessions, collaborating on solution architecture design, and assisting in proposal and statement of work creation.

- Contribute to the development of reusable, repeatable collateral for use across the practice.

- Obtain / maintain training and certification in cloud technologies.

- Work with the marketing team to produce content to promote the practice across the region.

Qualifications :

Key Requirements :

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

- 7-9 years of data engineering experience in data management, database architecture, data engineering, or data visualization.

- Excellent problem-solving, organization, debugging, and analytical skills.

- Ability to work independently and in a team environment.

- Excellent communication skills for effectively expressing ideas to team members and clients.

- Understanding of relational database concepts and SQL querying.

- Strong experience in Integrating with multiple data sources with both structured and unstructured data in both batch and streaming modes

- Knowledge of cloud computing platforms, such as Amazon Web Services (AWS), Google Cloud Platform (GCP), or Microsoft Azure.

- Experience building data pipelines with ETL tools/Equivalent Cloud services, such as Azure Data Factory, dbt, AWS Glue, Matillion or equivalent.

- Familiarity with data warehousing solutions, such as Amazon Redshift, Snowflake, Google BigQuery, or Azure Synapse.

- Experience with visualization tools, such as Power BI, Looker, Tableau, and QuickSight.

- Familiarity with Docker and Kubernetes

- Debug and optimize existing data infrastructure and processes as needed.

Nice To Have :

- Experience building large-scale, high throughput, 24x7 data systems.

- Any data engineering, visualization, or data science certifications on any of the clouds.

- Experience with at least one programming language, such as Python, Java, or Scala.

- Exposure to machine learning algorithms, AI, and/or LLM, with implementation in practice.

- Experience with legacy data systems (e.g. Hadoop, Informatica).