Job Purpose and Impact
We are seeking a skilled Data Engineer to design, develop, and maintain scalable data pipelines and platforms that enable reliable data ingestion, transformation, storage, and analytics. The ideal candidate will have strong expertise in cloud-based data engineering, ETL/ELT frameworks, data warehousing, and modern big data technologies
Key Accountabilities
Design and develop scalable data ingestion and processing pipelines.
Build and maintain batch and real-time data integration solutions.
Develop ETL/ELT workflows to transform and load data from various source systems.
Design and optimize data models for analytics and reporting.
Ensure data quality, integrity, governance, and security standards are maintained.
Monitor, troubleshoot, and optimize data pipelines and workloads.
Collaborate with product owners, business stakeholders, architects, and data scientists to deliver data solutions.
Implement data observability, monitoring, and alerting mechanisms.
Support cloud migration and modernization initiatives.
Create and maintain technical documentation, data lineage, and operational runbooks.
Qualifications
Have a Bachelor's degree with minimum 4 years of professional experience.
Experience with Snowflake, Databricks, Redshift, BigQuery, or Synapse.
Knowledge of Apache Kafka or other streaming technologies.
Experience with dbt and modern data stack tools.
Familiarity with DataOps and MLOps practices.
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Understanding of data governance, metadata management, and data quality frameworks.
Cloud certifications (AWS, Azure, or GCP) are preferred
Technical Skills
Programming: Python, SQL, Scala, Java
Data Processing: Spark, Hive, Airflow
Cloud: AWS (S3, Glue, Lambda, EMR), Azure, GCP
Databases: SQL Server, Oracle, PostgreSQL, Snowflake
Streaming: Kafka, Kinesis
DevOps: Git, Jenkins, CI/CD
Data Modeling: Star Schema, Snowflake Schema, Data Vault
