Data Engineer

New

Location: RemoteFull-TimeMiddle

Salary$110k to $140k annually

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Job Details

Experience: 4+ years of professional experience in data engineering or related domains
Required Skills: PostgreSQLPythonSQLApache AirflowJavaSparkdbtDatabricks

Bachelor's degree in Computer Science, Engineering, or a related technical field.
4+ years of professional experience in data engineering or related domains.
Strong hands-on experience with Databricks, Apache Spark (PySpark), Python, PostgreSQL, and dbt.
Experience building and maintaining AWS-native data platforms (Glue, EMR, Airflow, Lambda, S3, Redshift, RDS).
Proficiency with modern data lake technologies including Apache Iceberg and data formats (Parquet, ORC, Avro).
Experience with relational and NoSQL databases such as Oracle and GraphDB.
Knowledge of Java development and CI/CD practices using Harness.
Experience working in agile, iterative software development environments.
Strong analytical and problem-solving skills.
Excellent communication skills.

Design, build, and maintain scalable data pipelines, ETL/ELT workflows, and data models using Python, Apache Spark, Databricks, dbt, and SQL.
Develop and optimize AWS-native data platforms using Glue, EMR, Airflow, Lambda, Step Functions, S3, Redshift, RDS, and DMS.
Build ingestion and orchestration workflows using Apache Iceberg, Parquet, ORC, and Avro.
Develop cloud infrastructure using CloudFormation, GitHub, and CI/CD pipelines.
Support mission-critical analytics for federal data environments complying with FedRAMP and NIST 800-53 controls.
Lead modernization initiatives migrating legacy platforms like IBM DataStage and Hadoop to cloud-native AWS services.
Mentor junior engineers through technical guidance and code reviews.
Collaborate with cross-functional teams in an Agile environment.

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