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Growing your Engineering Career

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Datavant
March 30, 2023

(…without becoming a manager)

Russell Kirmayer joined Datavant as an engineer in October 2022 and has since become the manager of the Requester Experience Pod, working on building out a platform for retrieving medical records and connecting health data for patients. In his previous role, he worked on a variety of engineering teams at small, early-stage startups. Despite his move into engineering management, he acknowledges that the [engineer → manager] trajectory is not for everyone.
Are you an engineer looking to grow your career (with or without becoming an engineering manager)?
We’re hiring.

Datavant prioritizes growth over comfort. Keeping ourselves in the steep part of the learning curve is one of our core values. We’ve shared several articles on the Datavant Tech Blog describing the career paths of some of our engineers, like these about Anjali, Leon, and Carlos.

These stories all have a common narrative:

A pretty common narrative of professional growth in engineering.

This narrative seems to be a common one for engineers generally. If you’re trying to remain in a permanent state of professional growth, what do you do after becoming whatever it is your company determines to be a “senior” engineer? Answering that question earlier can help keep you on a path doing the kind of work you want to be doing.

The [engineer → manager] path is not the only path available to you. In this article, we’re going to explore some options to keep growing without becoming a manager, but first, let’s talk about managers.

What exactly is a manager, anyway?

There are more articles (…and webcomics, memes, movies, and tv shows) about good and bad management than there are bits of data on the entire internet.* In The Making of a Manager, Julie Zhuo describes the role of the manager as: “to get better outcomes from a group of people working together.” The manager is responsible for the output, not necessarily the specific activity or inputs.

*This is an unverified statistic.

According to Zhuo, getting better outputs happens across three areas of focus:

  • Purpose (the why): helping engineers understand why they are doing what they’re doing.
  • People (the who): helping engineers improve their own skills via training, coaching, feedback, and mentoring.
  • Process (the how): helping a team work together better to achieve greater than the sum of the individuals.

Managing includes a significant amount of administrative tasks (hiring and firing, handling compensation, team organization, etc.), the tradeoff for which is writing less code. We might summarize this tradeoff as transitioning from building/making to facilitating.

“I don’t need a manager anymore!”

There are common misconceptions out there about the relationship of engineers to managers, ideas like, “I don’t need a manager — I know what I’m doing, am good at my job, am fully autonomous, and don’t need feedback or advice!” or simply, “I don’t need to work with others, I just write my code.”

In addition to motivating a team, a great manager provides context and surfaces blind spots, which can help even experienced engineers increase the impact of their work. In a synergistic engineer / manager relationship, this becomes a positive feedback loop, with the engineer consistently seeking more context and feedback and the manager providing the right feedback at the right time to fill in whatever gaps are decreasing impact.

Synergistic IC / Manager relationship.

This cycle can occur no matter how senior the engineer is.

Maybe you’re a great engineer who contributes impactful work and your goal isn’t to manage, but to become a really great engineer who contributes really impactful work.

You don’t have to want to change careers in order to grow

There is significant incentive for companies to promote from within their own ranks, and Datavant is no exception in its focus on cultivating leadership from within, but as an engineer, it’s important to keep in mind that becoming a manager is tantamount to a career change.

Administrating, organizing teams, and bringing out the best work in people are particular skill sets that also demand commitment and development. This work is buttressed by your technical knowledge and experience building stuff, but it is no longer as much technical work. Some people are inclined toward managerial kinds of work and some are not. Maybe you’re a great engineer who contributes impactful work and your goal isn’t to manage, but to become a really great engineer who contributes really impactful work.

You are needed too. It’s important to remember that management and leadership are not the same thing. Managing is a specific set of tasks, but ICs can develop an impactful leadership profile without taking on the specific tasks of managing. A great engineer can use their knowledge and experience to lead from within their ranks and raise the skill and craft of their team just by interacting with the group in day-to-day functions.

If a company is sensitive to this, they will cultivate ways (possibly even independent of a title change) for engineers to increase the scope and complexity of problems they work on to keep them challenged and excited about their work.

Considering the options

Maybe you’re not entirely clear on the best non-manager path for you. Thinking holistically about the engineering organiztional structure and the priorities of each layer can help you define your own path.

  • A great Engineering Director focuses on building the team that coaches the teams, and excels at hiring great coaches who create winning teams.
  • A great Engineering Manager focuses on their team, and excels at building a team of IC’s and coaching individuals at their craft.
  • A great Engineer focuses on their craft, and excels at finding all possible ways to improve their skills while acting as a source of expertise for more junior engineers.

Breaking this down further, Will Larson describes several archetypes of non-managing engineers above the Senior level. These include the Tech Lead, Solver, Architect, and Right Hand. None of these are managerial roles, but they have significantly different profiles and specialties, and the structure of their week looks quite different.

In addition to thinking about what you’re good at, what kind of work excites you, and how you want to spend your time, you can continue to refine your ambitions with some further healthy introspection:

  • Do you enjoy focusing and becoming expert on a particular area like front end or React?
  • Do you enjoy hopping around different projects and moving things from 0–1?
  • Do you enjoy thinking about big picture and scale?
  • Do you enjoy “rallying the troops” or shipping big code yourself?
  • Do you enjoy specializing (depth) or being a generalist (breadth)?

On the last point, a useful way to think about the depth vs. breadth question is to think about the tradeoffs of each.

In the pursuit of depth, you invariably limit your field of study and so may have large areas you simply don’t know anything about. In the future, it may take longer to ramp up in one of these areas if you decide to move into it.

In going for breadth, you may know a little about a lot of things, but you may find yourself running into the limits of your skills more often. In the future, it may take longer to level up your entire skillset, because you can’t expand in all directions at once.

Defining, and then re-defining “impact”

Because you can only write so much code, non-manager engineers must redefine “impact” as they grow. How do you create an outsized influence and drive technical outcomes that are bigger than the code you write? For the increasingly senior IC engineer, this might be the fundamental question they must always be asking themselves. Some ways to do this might include:

  • Learn new design patterns / programming languages / frameworks
  • Look for ways to scale the team (eg. tools to multiply leverage)
  • Take on the hardest problems, learn a new domain (eg. SQL expert)
  • Look across pods, find common problems, create cross-pod learning
  • Read tech blogs / books / online class and bring back knowledge to share

Datavant currently has 6 levels for engineers, ranging from P0 (new grads making short code changes and fixing known bugs) to P6 (org-level engineers working on multi-month projects). To help the members of our team continue to move up that ladder, we have an “unlimited learning” policy, which means supporting educational opportunities, including but not limited to:

  • Online courses
  • Tech conference
  • Books
  • Anything you think will expand your skill set

Why it matters

Most people will spend 1/3rd of their adult life at work (~90,000 hours). Feeling like you are good at your job, feeling satisfied with the challenges you face, feeling like you contribute to your team, feeling a sense of progress, and owning your own growth aren’t just about being an impactful worker for your employer. These are fundamental questions about your life and how you use the time you have. Why not spend some time considering the possibilities and approaching this third of your life with the same intentionality you approach the other two thirds?

About the authors

Russell Kirmayer has a background in mechanical and software engineering and is the manager of the Requester Experience Pod. Connect with Russell via Linkedin.

Nicholas DeMaison writes for Datavant where he leads talent branding initiatives. Connect with Nick on LinkedIn.

Datavant’s engineering team is growing. Check out our open positions.

Spotlight on AnalyticsIQ: Privacy Leadership in State De-Identification

AnalyticsIQ, a marketing data and analytics company, recently adopted Datavant’s state de-identification process to enhance the privacy of its SDOH datasets. By undergoing this privacy analysis prior to linking its data with other datasets, AnalyticsIQ has taken an extra step that could contribute to a more efficient Expert Determination (which is required when its data is linked with others in Datavant’s ecosystem).

AnalyticsIQ’s decision to adopt state de-identification standards underscores the importance of privacy in the data ecosystem. By addressing privacy challenges head-on, AnalyticsIQ and similar partners are poised to lead clinical research forward, providing datasets that are not only compliant with privacy requirements, but also ready for seamless integration into larger datasets.

"Stakeholders across the industry are seeking swift, secure access to high-quality, privacy-compliant SDOH data to drive efficiencies and improve patient outcomes,” says Christine Lee, head of health strategy and partnerships at AnalyticsIQ. 

“By collaborating with Datavant to proactively perform state de-identification and Expert Determination on our consumer dataset, we help minimize potentially time-consuming steps upfront and enable partners to leverage actionable insights when they need them most. This approach underscores our commitment to supporting healthcare innovation while upholding the highest standards of privacy and compliance."

Building Trust in Privacy-Preserving Data Ecosystems

As the regulatory landscape continues to evolve, Datavant’s state de-identification product offers an innovative tool for privacy officers and data custodians alike. By addressing both state-specific and HIPAA requirements, companies can stay ahead of regulatory demands and build trust across data partners and end-users. For life sciences organizations, this can lead to faster, more reliable access to the datasets they need to drive research and innovation while supporting high privacy standards.

As life sciences companies increasingly rely on SDOH data to drive insights, the need for privacy-preserving solutions grows. Data ecosystems like Datavant’s, which link real-world datasets while safeguarding privacy, are critical to driving innovation in healthcare. By integrating state de-identified SDOH data, life sciences can gain a more comprehensive view of patient populations, uncover social factors that impact health outcomes, and ultimately guide clinical research that improves health. 

The Power of SDOH Data with Providers and Payers to Close Gaps in Care

Both payers and providers are increasingly utilizing SDOH data to enhance care delivery and improve health equity. By incorporating SDOH data into their strategies, both groups aim to deliver more personalized care, address disparities, and better understand the social factors affecting patient outcomes.

Payers Deploy Targeted Care Using SDOH Data

Payers increasingly leverage SDOH data to meet health equity requirements and enhance care delivery:

  • Tailored Member Programs: Payers develop specialized initiatives like nutrition delivery services and transportation to and from medical appointments.
  • Identifying Care Gaps: SDOH data helps payers identify gaps in care for underserved communities, enabling strategic in-home assessments and interventions.
  • Future Risk Adjustment Models: The Centers for Medicare & Medicaid Services (CMS) plans to incorporate SDOH-related Z codes into risk adjustment models, recognizing the significance of SDOH data in assessing healthcare needs.

Payers’ consideration of SDOH underscores their commitment to improving health equity, delivering targeted care, and addressing disparities for vulnerable populations.

Example: CDPHP supports physical and mental wellbeing with non-medical assistance

Capital District Physicians’ Health Plan (CDPHP) incorporated SDOH, partnering with Papa, to combat loneliness and isolation in older adults, families, and other vulnerable populations. CDPHP aimed to address:

  • Social isolation
  • Loneliness
  • Transportation barriers
  • Gaps in care

By integrating SDOH data, CDPHP enhanced their services to deliver comprehensive care for its Medicare Advantage members.

Providers Optimize Value-Based Care Using SDOH Data

Value-based care organizations face challenges in fully understanding their patient panels. SDOH data significantly assists providers to address these challenges and improve patient care. Here are some examples of how:

  • Onboard Patients Into Care Programs: Providers use SDOH data to identify patients who require additional support and connect them with appropriate resources.
  • Stratify Patients by Risk: SDOH data combined with clinical information identifies high-risk patients, enabling targeted interventions and resource allocation.
  • Manage Transition of Care: SDOH data informs post-discharge plans, considering social factors to support smoother transitions and reduce readmissions.

By leveraging SDOH data, providers gain a more comprehensive understanding of their patient population, leading to more targeted and personalized care interventions.

While accessing SDOH data offers significant advantages, challenges can arise from:

  • Lack of Interoperability and Uniformity: Data exists in fragmented sources like electronic health records (EHRs), public health databases, social service systems, and proprietary databases. Integrating and securing data while ensuring data integrity and confidentiality can be complex, resource-intensive and risky.
  • Lag in Payer Claims Data: Payers can take weeks or months to release claims data. This delays informed decision-making, care improvement, analysis, and performance evaluation.
  • Incomplete Data Sets in Health Information Exchanges (HIEs): Not all healthcare providers or organizations participate in HIEs. This reduces the available data pool. Moreover, varying data sharing policies result in data gaps or inconsistencies.

To overcome these challenges, providers must have robust data integration strategies, standardization efforts, and access to health data ecosystems to ensure comprehensive and timely access to SDOH data.

SDOH data holds immense potential in transforming healthcare and addressing health disparities. 

With Datavant, healthcare organizations are securely accessing SDOH data, and further enhancing the efficiency of their datasets through state de-identification capabilities - empowering stakeholders across the industry to make data-driven decisions that drive care forward.

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