Data Engineer Consultant

Job Description

Data Engineer Consultant (US Delivery Team)
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### The Opportunity

As a Data Engineer Consultant on our US team, you will build and deploy production-grade data pipelines for major enterprise clients. You will spend your day-to-day writing code, modernizing brittle legacy setups into cloud-native Lakehouses, and making client data clean, fast, and ready for AI applications.

In this role, you will work directly with modern technologies like **Databricks, dbt, Python, and Terraform**, collaborating with technical clients and our global engineering squads to ship solutions in weeks, not months.

### Key Responsibilities

* **Build Lakehouse Modernization Pipelines:** Convert legacy data setups (Informatica, PL/SQL, legacy data warehouses) into high-performance **PySpark** , **Databricks SQL** , and **Delta Live Tables (DLT)** using Medallion Architecture standards (Bronze, Silver, Gold).

* **Data Modeling \& Transformation:** Write clean, modular, and tested **dbt** models and advanced **SQL** to transform raw client data into trusted, business-ready datasets.

* **Automate Infrastructure (DataOps):** Use **Terraform** to provision cloud resources (AWS/GCP) programmatically and enforce data governance using **Unity Catalog**.

* **Integrate \& Orchestrate:** Build and monitor automated ELT/ETL workflows using tools like **Apache Airflow** and Databricks Workflows, ensuring data quality, lineage, and strict SLA compliance.

* **Client Engagement \& Collaboration:** Embedded directly within client projects, participating in daily standups, code reviews, and working closely with our nearshore delivery squads to deliver on time.

* **Troubleshoot \& Optimize:** Debug failing pipelines, tune complex SQL/Spark queries for performance, and reduce cloud computing costs for our clients.

### Qualifications \& Requirements

**Technical Stack**

* **Hands-On Data Engineering:** Strong background writing production code in **Python** and advanced **SQL**.

* **Databricks Experience:** Hands-on experience building on the Databricks Lakehouse platform (Delta Lake, PySpark, Unity Catalog, Workflows).

* **dbt Mastery:** Solid experience using **dbt** for data transformation, testing, and documentation.

* **Infrastructure as Code (IaC):** Practical experience writing **Terraform** scripts to deploy AWS or GCP cloud data infrastructure.

* **Orchestration \& Version Control:** Proficient with **Git** (GitHub/GitLab) for CI/CD workflows and experience with schedulers like **Airflow**.

**Consulting \& Delivery Mindset**

* **Client-Facing Comfort:** Ability to communicate technical decisions clearly to client teams and collaborate in a fast-paced consulting environment.

* **Problem-Solving Grit:** Ability to jump into unfamiliar legacy codebases, figure out how the data flows, and rebuild it cleanly without needing a rigid playbook.

* **Quality Focus:** Passion for writing testable, documented, and reusable code.

**Nice-to-Haves**

* Databricks, AWS, or dbt certifications.

* Experience working on migration projects from legacy warehouses (Teradata, Netezza, Snowflake, Redshift) to Databricks.

* Familiarity with streaming tools like Apache Kafka or CDC (Change Data Capture) pipelines.

*The anticipated base salary range for this role is $120,000 - $175,000. In addition to base pay, this position may be eligible for an annual discretionary bonus. An individual's final salary offer will be determined based on a variety of factors, including geographic location, experience, specialized skills, and qualifications. This compensation range is subject to updates or modifications at the company's discretion*