Lead data Engineer

About the Role :

Duration : 4-6 months

Location : Remote

Timings : Full Time (As per company timings)

Notice Period : (Immediate Joiner - Only)

Experience : 7+ Years

This is a hands-on leadership role where you'll guide the ongoing optimization of ETL infrastructure while also influencing broader platform improvements. You'll work closely with analysts, engineers, and leadership to ensure pipelines are reliable, efficient, and structured for long-term scale. This includes helping formalize data governance practices, evolving a light semantic layer, and enabling greater downstream automation of analysis and AI use cases.

You don't need to architect the future of the entire data platform—but you will help shape its direction and make it real.

What You'll Do :

Take ownership of pipeline stability and performance across the GCP-based stack (BigQuery, GCS, Dataprep / Dataflow)

Lead the enhancement of existing ETL workflows to support better modularity, reusability, and error handling

Help introduce lightweight governance practices—including column-level validation, source tracking, and transformation transparency

Support development of a semantic layer (e.g., KPI definitions, normalized metric naming) to reduce rework and support downstream users

Work with analysts and dashboard developers to structure data outputs for intuitive use and parameterization

Collaborate with team leadership to prioritize improvements based on impact and feasibility

Support platform readiness for automated reporting, predictive modeling, and AI-enhanced analysis

Contribute to team culture through clear documentation, mentoring, and code review

Participate in hiring, onboarding, and evolving internal standards

Must-Have :

7+ years of experience in data engineering, preferably in a fast-paced agency or multi-client environment

Solid command of Google Cloud Platform, especially BigQuery, GCS, and Cloud Dataprep (Alteryx) or Dataflow

Strong SQL and Python skills with a focus on transformation and data reliability

Experience building and maintaining ETL pipelines in production

Familiarity with metadata-driven development, version control, and task orchestration (Airflow or equivalent)

Proven ability to balance individual execution with team collaboration

Clear communicator, able to translate technical trade-offs to non-technical stakeholders

Nice-to-Have :

Experience applying basic data governance principles (e.g., lineage tracking, validation frameworks, naming conventions)

Exposure to building or maintaining a semantic layer (via dbt, LookML, etc.)

Familiarity with AI / ML workflows or tooling for automated insight generation

Understanding of marketing or media datasets

Experience developing custom marketing attribution models

Experience mentoring junior team members or participating in code / process standardization

Skills Required

Airflow, BigQuery, Alteryx, Google Cloud Platform, gcs , DataFlow, Python, Sql