Data Engineer - Real-Time Cloud Pipelines (Remote)

HRCap, Inc.; United States; On-site; USD 110,000 - 145,000; Full time

Benefits offered by this job

Performance Bonus

Equity Shares

Health & Wellness

Remote Work

Job summary

HRCap, Inc. seeks a data engineer to architect and maintain the enterprise data platform, building robust pipelines and cloud infrastructure that process millions of events daily.

You will optimize data warehouses and lakehouses (Snowflake, BigQuery, Redshift), ensure data quality with automated tests (Great Expectations, Datadog), and manage DAGs with Airflow, Prefect, or Dagster. Join a data-driven team shaping real-time analytics and scalable data services in a fast-growing cloud environment.

Qualifications

• Bachelor’s degree in CS/CE/IS or equivalent.
• 2–5 years professional data engineering experience in production cloud environments.
• Advanced SQL with query optimization, window functions, indexing, and profiling.
• Production-grade coding in Python/Scala/Java with OO/FP principles.
• Hands-on cloud infra experience in AWS or GCP (S3/GCS, EC2, IAM).
• Foundational knowledge of distributed data processing (Spark, Hadoop, Parquet).

Responsibilities

• Architect, write, and deploy resilient batch and streaming data pipelines using Python or Scala.
• Design and optimize schemas, tables, and partitions in Snowflake/BigQuery/Redshift.
• Implement automated data quality tests and monitoring (Great Expectations, Datadog).
• Author and manage DAGs with Airflow, Prefect, or Dagster.
• Collaborate on data models and governance, ensuring security standards.

Skills

Advanced SQL

Python/Scala/Java

Cloud platforms AWS/GCP

Airflow or workflow orchestration

Distributed computing concepts

Education

Bachelor’s degree in CS/CE/IS

Tools

Snowflake

BigQuery

Redshift

Apache Spark

Airflow

Dagster

DBT

Great Expectations

Datadog

Job description

HRCap, Inc. seeks a data engineer to architect and maintain the enterprise data platform, building robust pipelines and cloud infrastructure that process millions of events daily.

You will optimize data warehouses and lakehouses (Snowflake, BigQuery, Redshift), ensure data quality with automated tests (Great Expectations, Datadog), and manage DAGs with Airflow, Prefect, or Dagster. Join a data-driven team shaping real-time analytics and scalable data services in a fast-growing cloud environment.