Job Description:
- Design, develop, optimize, and maintain data architecture and pipelines that adhere to ETL principles and business goals.
- Solve complex data problems to deliver insights that help the organization achieve its goals.
- Code in Python with tools like Apache Spark to build a multi-cluster data warehouse.
- Interact with other technology teams to define, prioritize, and ensure smooth deployments for other operational components.
- Advise, consult, mentor, and coach other data and analytics professionals on data standards and practices.
- Foster a culture of sharing, reuse, design for scale stability, and operational efficiency of data and analytical solutions.
- Codify best practices for future reuse in the form of accessible, reusable patterns, templates, and code bases to facilitate data capturing and management.
- Strong experience in mapping attributes, data profiling, data cleansing, and technical data quality etc.
- Strong experience in Ansi SQL and in-depth knowledge with structured, semi-structured & unstructured data.
- Must have good knowledge of data lake and working experience of migration projects in cloud with providers like AWS or Microsoft AZURE or GCP.
- Good to have experience in working with No SQL, Spark SQL using AWS Glue, EMR, and columnar data store.
- Good to understand data security features like data masking, data encryption, role based & fine grain access control mechanisms etc.
Qualifications:
- 5+ years of relevant experience in data engineering/analytics space.
- Expertise in SQL and data analysis and strong hands-on expertise with at least one programming language: Python.
- Strong knowledge in one or more of the following big data tools: Hive, Hadoop Impala, Spark, Kafka.
- Strong expertise in ETL, reporting tools, data governance, data warehousing, and hands-on experience.
- Experience developing solutions for cloud computing services and infrastructure.
- Experience developing and maintaining data warehouses in big data solutions.
- Up to date on industry trends within the analytics space from a data acquisition processing, engineering, and management perspective.
- Experience in agile development.
- Strong people skills, specifically in collaboration and teamwork.
- High level of curiosity, creativity, and problem-solving capabilities.
