Junior Data Engineer

Job Title: Data Engineer (2+ Years Experience)

Location: Hybrid / Onsite / Remote

Experience Required: 2+ Years

Job Summary

We are seeking a skilled and motivated Data Engineer with 2+ years of experience in building scalable data pipelines, ETL workflows, and cloud-based data platforms. The ideal candidate will have hands-on experience with modern data engineering tools, distributed processing frameworks, and real-time streaming technologies, along with exposure to cloud ecosystems such as AWS, Azure, or Google Cloud Platform.

Key Responsibilities

• Design, develop, and optimize scalable data pipelines for batch and real-time processing.

• Build and maintain ETL/ELT workflows using tools like Databricks, Apache Spark, and dbt.

• Develop and manage data lakehouse architectures using Delta Lake, Iceberg, or similar technologies.

• Implement real-time data streaming solutions using Kafka, Kinesis, Flink, or Event Hubs.

• Work with cloud platforms (AWS, Azure, or Google Cloud Platform) to build robust and cost-efficient data solutions.

• Design and maintain data warehouses such as Snowflake, Redshift, or Synapse.

• Collaborate with data scientists and analysts to support data modeling, feature engineering, and analytics.

• Implement data orchestration using Airflow, Azure Data Factory, or similar tools.

• Ensure data quality, governance, and security using monitoring and validation frameworks.

• Automate infrastructure provisioning and deployments using Terraform and CI/CD pipelines.

Required Skills & Qualifications

• 2+ years of experience in Data Engineering or a related field.

• Strong programming skills in Python and SQL.

• Hands-on experience with Apache Spark / PySpark.

• Experience with ETL tools and workflow orchestration (Airflow, dbt, ADF, Glue).

• Familiarity with real-time streaming tools like Kafka, Kinesis, or Event Hubs.

• Experience working with cloud platforms: AWS, Azure, or Google Cloud Platform.

• Knowledge of data warehousing solutions such as Snowflake, Redshift, or Synapse.

• Understanding of data modeling, data lakes, and lakehouse architectures.

Preferred Qualifications

• Experience with MLOps tools such as MLflow, SageMaker, or Azure ML.

• Familiarity with containerization (Docker) and CI/CD tools (Jenkins, GitHub Actions).

• Exposure to data governance tools like Purview, DataHub, or Amundsen.

• Experience with BI tools such as Tableau, Power BI, or Looker.

• Knowledge of monitoring tools like Grafana, Datadog, or CloudWatch.

Education

• Bachelor’s or Master’s degree in Computer Science, Information Technology, or a related field.

Nice to Have

• Experience working in Agile environments.

• Strong problem-solving and communication skills.

• Ability to work in cross-functional teams and deliver business-driven data solutions.