
Big Data Specialist
6 days ago
Looking for a skilled Big Data Engineer to join our team. The ideal candidate should have a minimum of 5+ yrs. of experience in designing, developing and maintaining data pipelines.
About the role:
- Design, develop and maintain data pipelines for ingestion, transformation and storage of large-scale data.
- Work with Big Data ecosystems (Hadoop, Spark, Hive or similar) to process structured and unstructured data.
- Develop efficient ETL processes to integrate data from multiple sources into data warehouses/lakes.
- Write and optimize SQL queries for data validation, transformation and analytics.
- Collaborate with data analysts, data scientists and business stakeholders to understand requirements and deliver reliable solutions.
- Implement data quality, governance and security standards.
- Optimize data workflows for scalability and performance in production environments.
Requirements:
- Proven experience in Big Data technologies (Hadoop, Spark, Hive, HDFS, Kafka etc).
- Strong expertise in SQL (query optimization, stored procedures, complex joins).
- Hands-on experience with ETL tools/processes (Informatica, Talend, Apache NiFi, Airflow or custom ETL).
- Deep understanding of Data Warehousing concepts (star schema, snowflake schema, fact/dimension tables).
- Proficiency in programming languages like Python, Java or Scala (for data manipulation).
- Experience with cloud platforms (AWS Redshift, GCP BigQuery, Azure Synapse or Snowflake) is a plus.
- Strong problem-solving and debugging skills.
Preferred qualifications include experience in real-time data streaming, knowledge of containerization and orchestration, familiarity with DevOps practices and exposure to BI/reporting tools.
Why work with us?
- Work on innovative high-impact projects with a team of top-tier professionals.
- Continuous learning opportunities and professional growth.
- Flexible work environment with a supportive company culture.
- Competitive salary and comprehensive benefits package.
- Free healthcare coverage.
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