Accolite
Data Engineer
Job Description
Job Summary:
We are seeking a skilled and proactive Data Engineer with 3–8 years of hands-on experience in building and maintaining data pipelines. The ideal candidate will have strong expertise in Python, Apache Spark, and experience with Databricks or Snowflake. You will be a key contributor in transforming raw data into usable formats and enabling advanced analytics across the organization.
Key Responsibilities:
Design, develop, and maintain scalable and efficient data pipelines using Python and Spark.
Work on batch and real-time data processing solutions using Databricks or Snowflake.
Optimize data workflows for performance, reliability, and scalability.
Collaborate with data scientists, analysts, and stakeholders to understand data requirements.
Ensure data quality and integrity through validation, profiling, and monitoring.
Maintain documentation related to data pipelines, architecture, and infrastructure.
Troubleshoot and resolve issues in data pipelines and ETL processes.
Required Skills & Qualifications:
3–8 years of experience in Data Engineering or a related field.
Strong proficiency in Python for data engineering use cases.
Solid hands-on experience with Apache Spark (PySpark preferred).
Experience with Databricks or Snowflake (at least one is mandatory).
Strong understanding of data modeling, ETL/ELT concepts, and cloud data platforms.
Experience with version control (e.g., Git), CI/CD tools, and agile methodologies.
Familiarity with data security, privacy, and governance best practices.
Preferred Qualifications (Nice to Have):
Experience working with cloud platforms like AWS, Azure, or GCP.
Familiarity with Delta Lake, Airflow, or dbt.
Exposure to containerization tools (Docker/Kubernetes).
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