How to Set Effective Goals for Your Data Engineering Team

Like a well-oiled machine, an efficient data engineering team keeps everything in a business running smoothly.

A solid data engineering team can transform your business by building and maintaining the infrastructure that powers better data-driven decisions. But even with all their technical expertise, you won't get far without providing direction.

That's why setting achievable goals for your data engineering team is so important. The benefits of goal setting are clear: It keeps everyone aligned, focused, and working toward your company's broader objectives.

While there's no one-size-fits-all approach—because your goals will depend on factors like the types of data engineers you work with and your unique business needs—our step-by-step guide can help you set goals tailored to your team and your company.

Why Set Goals for Your Data Engineering Team?

In 1968, psychologist Edwin A. Locke introduced the goal-setting theory, which showed that employees perform better when they have clear, specific goals and constructive feedback.

It may seem obvious now, but back then, people were just realizing that vague instructions and reliance on luck and skill weren't effective.

Whether you're planning to assemble an in-house team, hire a remote data engineer, or implement a hybrid approach, setting goals helps your team stay organized, efficient, and focused. 

You should set goals for your data engineering team for the following reasons:

• Align with business priorities: Data engineers create the infrastructure that powers strategic decision-making. By setting goals, your team can focus on projects that directly support your business, whether that's speeding up data pipelines or improving access to key analytics.
• Improve cross-team communication: Clear goals create alignment across diverse teams, whether they're distributed remotely, working in-office, or comprised of both technical and non-technical members. By establishing shared objectives, professionals in data engineering roles can collaborate more effectively with other departments, reducing misunderstandings and keeping everyone moving in the same direction.
• Encourage accountability: Goals help everyone understand what's expected of them. This makes it easier to track progress and hold the team accountable while recognizing individual contributions and spotting areas for improvement.
• Support professional growth: Setting challenging but realistic goals encourages engineers to keep learning and expanding their skill set. For example, they might take on tasks involving new data platforms, cloud tools, or automation frameworks.
• Boost efficiency and focus: Goals also cut down on wasted effort. When engineers know what they're working toward, they can prioritize high-value tasks and avoid unnecessary busywork.

One of the top skills to look for when hiring a data engineer is adaptability—the ability to adjust as your business evolves. Goal-setting plays a big role in fostering that adaptability and ultimately improves employee engagement, which is key to a healthy, sustainable organization.

How to Set Effective Goals for a Data Engineering Team

Setting goals in the workplace is now considered standard practice. But for goals to work, they need to be well thought out and aligned with your company's needs and priorities.

This is especially true for a data engineering team, where the work is often technical and deeply connected to business outcomes.

Here are the key steps to setting data engineering team goals. 

1. Reflect on past performance

If you've been in business for a while, it's important to take a step back and evaluate how your team has been performing before setting new goals.

Which projects were completed successfully? Were there any delays or unexpected hurdles that got in the way? What kind of feedback have you received from other teams or stakeholders?

Reflecting helps identify areas where your team has excelled and where there's room for improvement. When you understand your team's strengths and weaknesses, you'll be in a much better position to set realistic and meaningful goals.

2. Align goals with business objectives

A data engineering team should support the broader goals of your business. That's why your team's goals should tie back to the company's overall strategy.

If your company's goal is to improve customer insights, your data engineering team might focus on enhancing real-time data processing to support that objective.

Aligning your team's goals with business needs also helps you decide how to structure your team. Some companies expand their full-time, in-house data engineering teams, while others choose to outsource data engineering to handle specific data tasks or projects.

3. Define measurable and actionable goals using the SMART framework

One of the most effective goal-setting frameworks is the SMART framework. It stands out from other methods by emphasizing quantifiable, time-bound objectives, making it easier to track progress and evaluate success.

Here's how setting SMART goals works:

• Specific: A vague goal like "improve data pipeline" won't help much. Instead, aim for something like "reduce data pipeline failures by 30% over the next six months."
• Measurable: Include metrics to track progress through various key performance indicators (KPIs).
• Achievable: Make sure the goal is challenging but still attainable given your team's resources and workload.
• Relevant: Ensure the data engineering team’s goal ties back to your business objectives so that your team can focus on what really matters.
• Time-bound: Set clear deadlines to create urgency and accountability.

Some relevant KPIs to data engineering include:

• Data pipeline uptime
• Data processing speed and latency
• Error rates and data quality metrics
• Infrastructure scalability
• Number of successful data integrations

4. Establish communication and integrate culture

Clear communication is key to keeping your team aligned and motivated. Online tools are especially important when operating remotely and managing teams across different time zones.

Here are a few ways to improve communication:

• Schedule regular check-ins to review progress and address any roadblocks.
• Use online collaborative tools like Slack, Asana, or Jira to keep everyone on the same page wherever they are.
• Document goals, key milestones, and expectations thoroughly.
• Encourage open communication by creating a safe space for feedback and new ideas.

Company culture also plays a significant role in your team’s performance. More than half of HR leaders believe managers fail to enforce their company's culture. A healthy work culture helps create a cohesive, engaged team that shares common values and works toward the same goals.

For instance, to improve teamwork, encourage team members to co-develop at least two key deliverables each quarter or participate in monthly knowledge-sharing sessions. Remote team building can also boost online collaboration and provide a change of pace from the usual routine. 

5. Monitor progress and adjust goals regularly

Finally, remember that goal-setting isn't a set-it-and-forget-it process. It's essential to re-evaluate goals and adjust them as necessary to keep your team on track.

This might mean revisiting goals every quarter to assess performance, identify obstacles, and make changes based on shifting business priorities. Regular discussions about the team’s progress also give your team a chance to celebrate their wins and stay motivated.

Final Thoughts

When your data engineering team has clear, measurable goals, they stay focused, motivated, and better equipped to deliver real value. Well-defined goals are especially important if you choose to hire remotely, as an aligned team can help overcome the challenges of working across locations and time zones.

Looking for an offshore data engineer to join your team? If you’re ready to take the plunge and hire outside of the US, you could open up new opportunities for talent and cost savings.

At Near, we connect businesses with top talent from Latin America (LatAm) through a comprehensive, personalized hiring process. Our remote LatAm data engineers offer a perfect blend of expertise and cost efficiency, with real-time collaboration for US companies.

Ready to learn more? Download our free LatAm hiring guide to explore the advantages, step-by-step process, and more, and start hiring smarter today.