Data Engineer (Python/SQL)

Introduction

Hakkoda, an IBM Company is a modern data consultancy that empowers data-driven organizations to realize the full value of the Snowflake Data Cloud. We provide consulting and managed services in data architecture, data engineering, analytics and data science. We are renowned for bringing our clients deep expertise, being easy to work with, and being an amazing place to work! We are looking for curious and creative individuals who want to be part of a fast-paced, dynamic environment, where everyone's input and efforts are valued. We hire outstanding individuals and allow them to thrive in a collaborative atmosphere that values learning, growth, and hard work. Our team is distributed across North America, Latin America, and Europe. If you have the desire to be a part of an exciting, challenging, and rapidly growing Snowflake consulting services company, and if you are passionate about making a difference in this world, we would love to talk to you!.

In this role, you'll work in one of our IBM Consulting Client Innovation Centers (Delivery Centers), where we deliver deep technical and industry expertise to a wide range of public and private sector clients around the world. Our delivery centers offer our clients locally based skills and technical expertise to drive innovation and adoption of new technology.

Your role and responsibilities

What we are looking for:

We are in search of a skilled Consultant Data Engineer to join our expanding team of experts. This role will be pivotal in the design and development of Snowflake Data Cloud solutions, encompassing responsibilities such as constructing data ingestion pipelines, establishing sound data architecture, and implementing stringent data governance and security protocols.

Key Responsibilities

Data Pipeline & Engineering Execution

• Develop and maintain scalable data pipelines and ingestion processes using SQL, Python, dbt, and cloud-native tools.
• Implement ELT/ETL patterns across batch, incremental, and CDC pipelines.
• Build data models using best practices in Dimensional modeling, Data Vault, or Lakehouse approaches.
• Support the development of data transformations, data quality validations, and business logic implementations.

• Work with cloud platforms (Snowflake, Databricks, AWS, Azure, or GCP) to build high-performance, cost-efficient data solutions.
• Implement warehouse/lakehouse structures, storage standards, schema management, and governance rules.
• Assist with orchestration using Airflow, dbt Cloud, or similar tools.

• Collaborate with client stakeholders to clarify requirements and translate them into actionable engineering tasks.
• Communicate progress, technical decisions, and blockers clearly and professionally.
• Participate in client demos, stand-ups, and architecture discussions, representing Hakkoda's engineering excellence.
• Document technical solutions and contribute to handover materials.

• Implement data validation and monitoring logic to ensure accuracy and reliability.
• Follow security best practices including RBAC, data masking, encryption, and compliance requirements.
• Contribute to documentation, standards, and engineering templates.

• Work closely with senior engineers and architects to design and refine solutions.
• Participate in code reviews and adopt Hakkoda's engineering standards.
• Mentor junior engineers as needed and support internal knowledge-sharing sessions.
• Contribute to internal accelerators, playbooks, and reusable assets.

• Stay current on cloud, data engineering, Snowflake, Databricks, and modern data stack technologies.
• Explore new tools, patterns, and methodologies that improve engineering efficiency.
• Bring new ideas to the team and participate in innovation initiatives at Hakkoda.

• 4+ years of experience in Data Engineering or similar roles.
• Strong SQL skills and hands-on experience building data pipelines.
• Proficiency with Python or a similar programming language.
• Experience with at least one cloud data platform (Snowflake, Databricks, BigQuery, Redshift, or Synapse).
• Familiarity with data modeling concepts (Dimensional, Data Vault, Lakehouse).
• Hands-on experience with version control (GitHub, Bitbucket) and CICD workflows.
• Experience working in agile, collaborative environments.