Data Engineers understand the fundamentals of how to create a robust and efficient infrastructure that makes data accessible and ready for analysis for our clients. Because our clients are mostly US-based organizations, we look for the ability to communicate with professional proficiency in English, verbally and in writing.

Functional Skills & Knowledge: You are responsible for building the infrastructure to support the storing and movement of data, so that it can be prepared by analytics engineers to eventually be interpreted by analysts. Your job is data accessibility, enabling our clients to utilize data for performance evaluation and optimization.

• Designs and maintains data pipelines, cloud data warehouse, and storage solutions.
• Has the working knowledge and skills to ensure best practices in data quality, manage ETL (Extract, Transform, Load) / ELT processes, and establish data architecture.
• Has a solid understanding of discipline basics, wherein you can competently execute on smaller analytics tasks or product improvements with the guidance of senior engineers and management. You can consistently deliver small features and improvements that have an impact on clients.
• Provides constructive feedback on peer code or technical design document reviews
• With career development:
  • Participates in design and bug fixes under direct supervision. Writes, tests, and documents code as per BDC guidelines, writing and reviewing technical design documentation.
  • Confidently contributes to internal analytics projects, eventually improving our in-house approach by regularly planning technical work with the team.
  • Independently leads small- to medium-sized projects (4-8 analytics weeks) through the entire lifecycle from design to development and deployment.
  • (Over time) Serves as a mentor for less advanced team members and onboarding new engineers onto the team.

 

Cross-Team Collaboration: You are responsible for collaborating with peers and senior ICs in other functional departments—most often data solutions, analytics engineering, and data analytics—to develop and implement data engineering approaches that support our client engagement goals.

• Effectively collaborates across disciplines, including data analytics and analytics engineering.
• Collaborates with analytics engineers to design efficient data pipelines.
• Support other functions by building CI/CD workflows or other supporting components to enable them to deliver their work quickly and efficiently.
• Approaches problem-solving as a team effort, providing timely and helpful feedback to peers and leads.
• Works well with other members of the team and are comfortable challenging other people’s opinions and open to having their own opinions challenged, too.
• Regularly seeks feedback from other team members (other Engineers, Data Solutions Managers, and peers in other functions) and incorporates that feedback in day-to-day work.

 

Engagement Delivery: You are responsible for ensuring that smaller and/or lower complexity data engineering projects are delivered on time, within scope, and within budget.

• Consistently seeks out, delivers and maintains small projects or surface-specific tasks with the help of more experienced Engineers.
• Capable of self-directed project delivery and can help the team to prioritize work that maximizes team impact, including avoiding getting stuck on unimportant details.
• Participates in the definition and delivery of work or projects within the team.
• Escalates matters when appropriate without getting into rabbit holes or blocked for long time periods. Exercises a good sense of timeboxing tasks and is able to proactively address issues before they become problematic.

Tools & Technologies

• Programming languages (e.g. SQL, Python)
• Data Processing (e.g. Apache Spark, dbt)
• Cloud-based data warehouses (e.g., Snowflake, Google BigQuery)

Technical Skills (Hard Skills)

See the latest Data Engineering framework.

• Data Movement: You can import large, assorted datasets from multiple sources into a single storage medium, wherein you understand event-driven architectures and asynchronous pub/sub design patterns.
• Data Warehousing: You have a solid working knowledge of how to effectively collect, organize, and manage large sets of data from multiple sources toward generating insights and supporting decision-making. You can independently provision a warehouse and perform medium complexity administrative tasks (e.g. working with permissions).
• Programming: You have a practical understanding and background in programming, as evidenced by the ability to maintain local development environments, contribute basic features (unit testing, following clear steps for completion), and write code thoughtfully to aid in testing and modularity.
• Domain Expertise: You have a strong foundation of knowledge in domains in which you’re working. You are able to relate how the business works with the goals of the immediate team.

 

Bonus points for:

• Data Modeling & Transformation: You have a solid working knowledge of how to convert, cleanse, and structure data into usable formats/structures to prepare it for analysis. You can effectively transform raw data into analysis-ready models for different use cases.
• Data Infrastructure: You have a working knowledge of how to design, build and maintain efficient systems using architecture components (DWH, VMs, storage buckets, etc.) as an infrastructure-as-code solution (Terraform, Pulumi), networking settings to appropriately secure access, and different storage tiers and life cycles of blob storage solutions.

Essential Skills (Intangible Skills)

• Organizational Accountability: You can manage your own time in consultation with others, effectively delivering individual tasks and assignments.
• Curiosity & Versatility: You are generally comfortable with new contexts and roles and can point to multiple occasions where you’ve changed approach or tools quickly and efficiently in response to a situation.
• Collaboration & Partnership: You can reliably assist and support the facilitation of meetings and collaborative projects with team members and occasionally engage in discussions with external stakeholders, if needed.
• Effective Communication: You usually communicate effectively, clearly, concisely and in an audience-oriented way, actively listening to others to ensure understanding.

Qualifications (Must Haves)

• Proven experience as a Data Engineer or related role, with a focus on designing and developing data pipelines.
• Strong programming skills in languages such as Python, Rust, Scala, or SQL.
• Deep knowledge of data warehousing and ETL/ELT processes.
• Hands-on experience with data warehouses like Snowflake, BigQuery, Databricks, or similar.
• Experience with streaming solutions such as Spark Streaming, Kafka, or Flink is desirable but not required.
• Familiarity with cloud platforms such as AWS, Azure, or Google Cloud.
• Familiarity with machine learning operations (MLOps) techniques and platforms is a plus but not required.
• Strong analytical and problem-solving skills.
• Excellent communication and collaboration skills

 

Physical Requirements

• Frequent sitting at a desk performing work on a computer
• Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions

Core Company Values

 

Miaz-Techis an established mid-sized agency with a top-tier portfolio of clients, ranging from the world’s largest non-profits to Fortune 500 brands. We pride ourselves on our people-first culture and a low-ego workplace that embraces experimentation, collaboration and continuous improvement. We have a fun office environment located in Davis Square (Somerville, MA) and offer competitive pay and excellent benefits.

• Take the Long View – Ensure the company is built to last
• Be Courageous – Make the right decisions even when they aren’t the easiest decisions
• Be Genuine – Bring honesty and authenticity to all that you do
• Work with Focus + Passion – Display purpose and pride in your work and never stop learning

 

As an equal opportunity employer, we are firmly committing to diversity, equity, and inclusion in our hiring efforts. We recognize that we need team members from all backgrounds and experiences to successfully shape a positive employee experience as well as deliver our product and service solutions. To that end, we actively seek candidates who can bring diverse experiences and backgrounds to our team. We know that complex factors and systemic bias can get in the way of us meeting strong candidates, so please don’t hesitate to apply even if you’re not 100% sure.

 

At this time, Miaz-Tech does not sponsor candidates and unfortunately cannot accept those on OPT or CPT.

 

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