Data Engineer

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

Benefits offered by this job

Performance Bonus

Equity Shares

Remote Work Perks

Premium Health & Wellness

Job summary

HRCap, Inc. is seeking an Analytical Data Engineer to design, build, and maintain high-scale data pipelines and cloud infrastructure that process millions of daily events. You will enable data scientists, analysts, and production AI models with clean, optimized data.

You will own the data foundation, optimize pipelines to reduce cloud costs, and enable real-time reporting across a modern cloud stack including Snowflake, BigQuery, Redshift, Spark, Kafka, and DBT.

Qualifications

• Bachelor’s degree in Computer Science or a related technical discipline.
• 2–5 years of professional data engineering experience in a production cloud environment.
• Expert-level mastery of SQL with query optimization and profiling.
• Proficiency in Python, Scala, or Java and modern software practices.
• Hands-on experience with AWS or GCP cloud services (S3, EC2, IAM, Cloud Functions).
• Foundational knowledge of distributed data processing (Spark, Hadoop) and Parquet formats.

Responsibilities

• Architect, write, and deploy resilient ETL/ELT pipelines in batch and streaming modes.
• Design and optimize schemas in Snowflake, BigQuery, and Redshift for performance.
• Implement automated data quality and observability using tools like Great Expectations or Datadog.
• Create and maintain DAGs in Airflow, Prefect, or Dagster for complex workflows.
• Collaborate on data modeling and governance with engineers and analytics teams.

Skills

SQL expertise

Python

Scala/Java

Data pipelines

Education

Bachelor’s degree in Computer Science or related field

Tools

Snowflake

BigQuery

Redshift

Airflow

Kafka

DBT

Spark

Datadog

Great Expectations

Terraform

Docker

Kubernetes

Job description

Our client is a high-growth, data-centric technology enterprise managing high-velocity data transactions for millions of global users. We are seeking an analytical, systems-minded Data Engineer to serve as a key architect behind our enterprise core data platform. In this role, you will be responsible for designing, building, and maintaining the robust data pipelines and cloud infrastructures that ingest millions of daily events. You will ensure that raw data is transformed into clean, highly optimized, and democratized structures, empowering downstream data scientists, analysts, and production AI models with flawless information.

Why Join Us

• Enterprise Data Scale: Move past standard data warehouses to engineer pipelines that ingest, parse, and process petabyte-scale data lakes running in real time.
• Modern Cloud Data Stack: Deepen your technical expertise by working directly with premier distributed systems and data tooling, including Apache Spark, Airflow, Snowflake, Kafka, and DBT.
• Direct Business Impact: You will own the foundation of our data strategy. Your pipeline optimizations will directly reduce cloud computing costs and unlock real-time business critical reporting.

Responsibilities

• Pipeline Engineering (ETL/ELT): Architect, write, and deploy resilient batch and streaming data pipelines using Python or Scala to extract, transform, and load data from transactional databases, webhooks, and third-party SaaS APIs.
• Data Warehouse & Lakehouse Optimization: Design and optimize schemas, tables, and partitions within cloud data warehouses (e.g., Snowflake, BigQuery, Redshift) to reduce query latencies and maximize storage efficiency.
• Data Quality & Observability Automation: Implement automated testing frameworks and monitoring alerts (using tools like Great Expectations or Datadog) to proactively detect data drift, schema changes, and pipeline anomalies.
• Workflow Orchestration Management: Author, schedule, and maintain complex, dependency-aware Directed Acyclic Graphs (DAGs) using workflow management tools like Apache Airflow, Prefect, or Dagster.
• Data Modeling & Governance: Collaborate closely with backend engineers and analytics teams to design logical data models (e.g., Star Schema, Data Vault 2.0), enforce data governance policies, and ensure strict compliance with global security standards.

Requirements

• Education & Engineering Literacy: Bachelor’s degree in Computer Science, Computer Engineering, Information Systems, or an equivalent technical discipline with a strong emphasis on distributed systems and databases.
• Professional Experience: 2 to 5 years of proven professional experience as a dedicated data engineer or backend platform developer operating in a production cloud environment.
• Advanced SQL Command: Expert-level mastery of SQL, with a deep understanding of query optimization, window functions, complex indexing, and profiling execution plans.
• Programmatic Software Foundations: Strong proficiency writing clean, testable production code in Python, Scala, or Java, applying object-oriented or functional programming principles.
• Cloud Infrastructure Fluency: Practical, hands‑on experience utilizing core services within major cloud ecosystems—specifically AWS or GCP (e.g., S3/GCS, EC2/Compute Engine, IAM, Cloud Functions).
• Distributed Computing Exposure: Foundational knowledge of distributed data processing concepts and storage architectures (e.g., Apache Spark, Hadoop, Parquet formats).

Preferred Qualifications

• Prior experience utilizing data build tools for managing analytics engineering transformations.
• Hands‑on experience with streaming architectures and message brokers (such as Apache Kafka, Amazon Kinesis, or RabbitMQ).
• Familiarity with infrastructure-as-code software (Terraform) and container orchestration tools (Docker, Kubernetes).
• Employment Type: Full-Time, Permanent
• Salary Range: $110,000 - $145,000 base structure + Performance Bonus, Equity Shares & Premium Corporate Health, Wellness, and Remote Work Perks.