Principal Software Engineer

About You – experience, education, skills and accomplishments 

Bachelor’s degree in computer science, Information Technology, or a related field, or equivalent experience

Atleast 10 years of experience as a Data Engineer or Architect.

Experience with structured and unstructured data, including relational databases, NoSQL, data lakes, and distributed storage.

Familiarity with cloud platforms (AWS must and GCP, Azure good to have) and their data services.

Proficiency in programming languages like Python, Java, or Scala.

Experience with source formats: XML, HTML, XSLT, Unicode, DTDs, XML Schema, XQuery, XPath, PDF, TIFF and similar formats.

Knowledge of data modelling and data governance concepts.

It would be great if you also had… 

Experience with data streaming technologies (e.g., Kafka, Spark Streaming).

Experience with data warehousing and ETL/ELT tools (e.g., Snowflake, Redshift, Databricks).

Familiarity with machine learning algorithms and data visualization tools.

Knowledge of intellectual property (IP) would be advantageous

What will you be doing in this role? 

Data Architecture Design: Develop and implement scalable and efficient data architectures to support analytics and data science initiatives.

Data Pipeline Development: Build and optimize data pipelines for collecting, processing, and storing large datasets from various sources.

Cloud Infrastructure: Manage and optimize cloud data services (AWS, Google Cloud, Azure) and ensure proper configuration, scalability, and cost-effectiveness.

Data Quality: Implement and maintain data quality standards and processes to ensure data accuracy, consistency, and completeness.

Performance Tuning: Monitor and optimize data processing workflows and database performance.

Collaboration: Work closely with data analysts, data scientists, and other stakeholders to understand data requirements and provide solutions that meet business needs.

Mentorship: Provide guidance and mentorship to junior data engineers and help in building a strong data engineering culture within the organization.

Stay Updated: Keep abreast of industry trends, tools, and best practices in data engineering and architecture.