Senior Consultant – Modern Data & Analytics Engineering

Are you driven by the challenge of turning complex, fragmented data into scalable solutions that people can trust and use? Do you enjoy working across architecture, engineering, analytics, and business teams to solve problems from end to end?

Torq is looking for experienced data engineers and architects who combine strong technical skills with consulting judgment and a focus on business outcomes.

At Torq, our data engineers are not limited to one layer of the technology stack. You will help clients navigate the full data lifecycle - from source-system analysis and data acquisition through integration, modeling, governance, quality, analytics, and production support. You will design and build modern data platforms that enable better reporting, faster decisions, operational efficiency, advanced analytics, and AI.

This role is ideal for someone who is comfortable getting hands-on with technology, leading technical workstreams, and explaining complex architecture decisions to both technical and business stakeholders.

What you Could be Doing:

Lead technical workstreams across data platform modernization, cloud migration, enterprise integration, analytics, and AI-enablement initiatives.

Assess existing data ecosystems, identify architectural and engineering constraints, and define practical modernization recommendations.

Design scalable cloud-based data architectures, including data lake, lakehouse, warehouse, data mesh, and data-product patterns.

Build and optimize batch, near-real-time, streaming, and API-based data integrations across enterprise source systems.

Develop reliable ETL and ELT pipelines using modern engineering frameworks, orchestration tools, and cloud-native services.

Design conceptual, logical, and physical data models that support operational reporting, business intelligence, analytics, and AI use cases.

Partner with business analysts, product owners, data consumers, and subject-matter experts to translate requirements into durable technical solutions.

Establish data quality controls, reconciliation processes, monitoring, observability, and operational support procedures.

Implement metadata, lineage, security, privacy, and governance requirements as part of the engineering lifecycle.

Apply software engineering practices - including version control, automated testing, code review, documentation, and CI/CD - to data solutions.

Evaluate technology options, document architectural decisions, and communicate tradeoffs clearly to client stakeholders.

Troubleshoot complex data issues across source systems, pipelines, models, platforms, and reporting layers.

Guide junior consultants and engineers by reviewing work, sharing context, and improving the quality and consistency of technical delivery.

Contribute to Torq accelerators, reusable frameworks, reference architectures, engineering standards, and technical enablement.

Support business development by identifying client needs, shaping technical solutions, estimating delivery efforts, and contributing to proposals and presentations.

What You Bring to the Table:

When you join Torq, you are a consultant first. That means understanding the business problem behind the request, bringing structure to ambiguity, communicating clearly, and taking ownership for delivering a successful outcome.

At the Senior Consultant level, we expect you to independently lead meaningful pieces of work, build credibility with client stakeholders, and remain actively involved through delivery.

Core Consulting & Leadership Strengths:

Ideally 5+ years of experience in data engineering, data architecture, analytics engineering, cloud data platforms, or related technical and analytical work.

Experience working in consulting, professional services, or another client-facing delivery environment is strongly preferred.

Strong problem-solving skills and the ability to break ambiguous business and technical challenges into practical solutions.

Ability to lead a technical workstream, manage priorities and dependencies, and deliver high-quality work with limited oversight.

Strong written and verbal communication skills, including the ability to explain complex technical concepts in business-friendly language.

Experience collaborating with data consumers, business stakeholders, application teams, infrastructure teams, security teams, and executive sponsors.

Ability to balance technical quality, delivery timelines, client priorities, and long-term maintainability.

A four-year degree in Computer Science, Data Science, Information Systems, Engineering, or a related field, or equivalent professional experience.

Technical Experience:

Advanced SQL skills and experience designing efficient solutions for large and complex datasets.

Experience with Python, Spark, Java, Scala, or another language commonly used for data engineering.

Hands-on experience designing and developing ETL or ELT pipelines using tools such as dbt, Apache Airflow, Azure Data Factory, Fabric Data Factory, Databricks Workflows, AWS Glue, or comparable technologies.

Experience with one or more major cloud environments: Microsoft Azure, Amazon Web Services, or Google Cloud Platform.

Experience with modern data platforms such as Microsoft Fabric, Databricks, Snowflake, Synapse Analytics, BigQuery, or Redshift.

Strong knowledge of dimensional modeling, normalized modeling, semantic models, data vault, medallion architectures, and related data-design patterns.

Experience acquiring data through APIs, files, relational databases, SaaS platforms, event streams, and other enterprise sources.

Understanding of data security, access control, privacy, governance, metadata, lineage, and lifecycle-management concepts.

Experience applying Git, automated testing, infrastructure as code, deployment pipelines, and CI/CD practices to data solutions.

Familiarity with reporting and analytics platforms such as Power BI, Tableau, Looker, or comparable tools.

Hands-on experience with Adobe Analytics and/or Google Analytics 4.

Experience with customer data concepts such as Customer 360, identity resolution, unified customer profiles, segmentation, audience activation, and customer lifetime value.

Additional Experience We Value:

We do not expect every candidate to have all of the following, but experience in one or more of these areas is a plus:

Customer Data Platforms (CDPs)

Adobe Analytics, Google Analytics 4, Adobe Customer Journey Analytics, or similar digital analytics platforms

Salesforce Data Cloud, Salesforce Marketing Cloud, Microsoft Dynamics 365 Customer Insights, Segment, Tealium, Treasure Data, or other customer data platforms.

Microsoft Fabric and OneLake

Azure Databricks or Databricks on AWS

Snowflake and Snowpark

Delta Lake and lakehouse architecture

Kafka or other event-streaming technologies

Terraform or other infrastructure-as-code tools

Microsoft Purview, Unity Catalog, Collibra, or Informatica

Data mesh and data-product operating models

Master data management and reference data management

Data observability, automated data quality, and platform monitoring

Semantic modeling and advanced Power BI development

Machine-learning and generative-AI data pipelines

Vector databases, unstructured-data processing, retrieval-augmented generation, and AI-ready data architecture

Experience in automotive, airline, insurance, financial services, energy, healthcare, or consumer services

Benefits and Other Fun Stuff:

We ask our consultants to be superstars, so we treat them like it. Even better, our perks are designed for employees by our employees. We do this because we believe in delivering a compelling benefits package that puts you at the heart of our rewards!

Competitive Salary – your bank account will be smiling

Unlimited PTO – we’re serious about that work-life balance thing

Best-in-class health/vision/dental b