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Data Engineer
Job Description
Key Responsibilities
- Design, develop, and maintain scalable ETL pipelines and DataOps workflows
- Build robust processes to integrate internal and external data sources with quality checks
- Automate manual tasks and optimize data ingestion and delivery processes
- Collaborate with cross-functional teams including product, marketing, and business development
- Support technology teams in evaluating and setting up tools for data governance and analytics
- Drive innovation in data infrastructure, quality, and reporting standards
Requirements
Experience & Education
- Minimum 2 years of experience in data engineering
- Open to candidates from any academic background with relevant experience
Technical Expertise
- Proficiency in building scalable data pipelines and warehouses
- Experience with Python, Scala, PySpark, or PL/SQL
- Hands-on experience with cloud platforms (e.g., AWS, S3, Redshift, Glue, etc.)
- Familiarity with distributed systems (e.g., Hadoop, Spark), NoSQL databases, and cloud data warehouses (e.g., Snowflake, BigQuery)
Personal Attributes
- Strong problem-solving and analytical skills
- Entrepreneurial mindset and initiative-driven
- Excellent communication and collaboration skills
- A team player who supports others and contributes positively to team culture
More Info
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Key Skills
About Company
Skills:
Data Modeling, Sql, data pipeline development, Snowflake Data Warehouse, ETL processes, data quality frameworks, database design principles, data querying techniques, data governance practices
Skills:
Java, Distributed Systems, Hadoop, Scala, Big Data, Shell Scripting, Svn, Git, Docker, Linux, Ansible, Openshift, Agile Development, Databricks, Azure, Kubernetes, Python, AWS, Source Code and Version Control systems, cloud platforms, infrastructure automation, CI CD pipelines, horizon
Skills:
data engineering , Power Bi, Power Automate, Data Warehousing, Data Integration, Sql, Power Apps, data modeling best practices, API data integration, error logging, error handling
Skills:
data engineering , Databricks, Python, Sql, AWS, Etl, CI-CD orchestration
Skills:
unstructured data , AI ML, Data Quality, embeddings, vector search, Generative AI, data pipelines, vector databases, data infrastructure, data engineering solutions, AI-assisted software development tools, modern AI ML engineering practices, Document Processing, AI-powered software development tools, LLM-based applications, semantic search, data quality monitoring